When submitting papers to scientific journals, it makes sense to aim slightly above the paper’s level – after all, if you submit too high, you get rejected and can resubmit, while if you submit too low you end up just publishing there. Or so it seems to me.

An extreme strategy (which is equally impractical and evil) would be to make a list of all journals ranked from best to worst, and keep submitting to the highest ranking one that you haven’t tried yet, until one of them accepts. With a strategy like that, the chance that the paper gets accepted in any particular submission is close to zero. At the other end of the spectrum, if almost all of your submissions are accepted then it’s very likely that you’re selling yourself short.

Now, it’s impossible to know with any level of precision what’s the probability of acceptance of a given paper at any particular journal. But it is possible to observe a general trend, and try to adjust your confidence up or down. Hence, the question:

If one is reasonable in their choice of journals, how frequently should their papers be rejected?

In other words, at what point should I start making a conscious effort to submit to better journals? At which point should I start submitting to worse journals?

For instance, my current strategy is to try and figure out how good a paper is, and first submit to a journal that’s about the best that could possibly accept it, and then go down from that by a small but noticable margin. In a small sample size, about half the time the paper was submitted on the first attempt, and about half the time on the second, and so far I haven’t had to submit anything three times. Hence, my papers get rejected around 33% of the time. Is this a reasonable frequency, or should I be more modest (or possibly more aggressive) in my choice of journals?

My field is pure mathematics, but I’m also interested in perspectives from other fields.

So I finished my degree recently, plus close to a years worth of research prior and continuing to work through the summer all to go towards a paper I was hoping would be submitted earlier this year. The story, data and conclusions were all neatly wrapped up and the paper was basically there, but the fact I left to start a job meant that the priority level for getting it submitted plummeted.

Flash forward to now, I haven’t had any contact regarding the paper for months and received a message from a current student who just finished saying that they want to now piece their data into my paper to ‘give a more complete picture’. This concerns me regarding authorship, considering I showed the student experimental protocols that I developed during my undergrad and from what I can see hasn’t collected as much data as I have. Personally, I feel it would be unfair to award a joint lead authorship if it ended up flopping that way if the story were to shift in direction. Again, I know very little as I haven’t been communicated with for a while.

Can anybody share some perspectives regarding this? Separating personal frustration about credit sharing aside, is there any downside to my own career regarding sharing lead authorship? This would also be my first paper.

Thanks

In a colloquium, an eminent senior professor showed a graph from a peer-reviewed journal (published by some other group). The graph contained three curves:

  1. black dots (blurred)
  2. black line (blurred)
  3. red line (thick and bright)

All these curves in the graph reports the same property (obtained with different methods).

When talking about the graph, the speaker mentioned, “Since the authors thought that this data (by pointing the red line) is most important, they have used red line”

My question is, is there such custom in plotting graphs?

Note: I ask this question because, in Origin Software, the first and second curve are, by default, black and red. If those colors are used, it may given an impression that the red line graph is the better result (compared to black line graph).

Recently, a well established senior professor showed a graph (other group’s paper published in Physical Review Letters) in a weekly colloquium. The graph contained three curves:

  1. black dots (blurred)
  2. black line (blurred)
  3. red line (thick and bright)

All these curves in the graph reports the same property (obtained with different methods).

When talking about the graph, the speaker mentioned, “Since the authors thought that this data (by pointing the red line) is most important, they have used red line”

My question is, is there such custom in plotting graphs?

So I finished my degree recently, plus close to a years worth of research prior and continuing to work through the summer all to go towards a paper I was hoping would be submitted earlier this year. The story, data and conclusions were all neatly wrapped up and the paper was basically there, but the fact I left to start a job meant that the priority level for getting it submitted plummeted.

Flash forward to now, I haven’t had any contact regarding the paper for months and received a message from a current student who just finished saying that they want to now piece their data into my paper to ‘give a more complete picture’. This concerns me regarding authorship, considering I showed the student experimental protocols that I developed during my undergrad and from what I can see hasn’t collected as much data as I have. Personally, I feel it would be unfair to award a joint lead authorship if it ended up flopping that way if the story were to shift in direction. Again, I know very little as I haven’t been communicated with for a while.

Can anybody share some perspectives regarding this? Separating personal frustration about credit sharing aside, is there any downside to my own career regarding sharing lead authorship? This would also be my first paper.

Thanks

I have been working on a particular algorithm. It has many applications and I have found one for which a dataset is available as well as other algorithms used to parse that dataset. But the algorithm I am studying hasn’t been applied to that dataset as far as I know. If I implement that algorithm on the dataset, I don’t think I will be making significant changes to it. Will it still be considered as enough of a result to publish a paper?

I am an undergrad; if that is relevant.

I am writing a research paper about discovery of a new data structure. From here (question a), here, and here I have inferred that I should not publish actual code in the paper, but instead use pseudocode.

I have been busy translating my object-oriented code (written in C#) to pseudocode for my paper. Here’s the C# for one method I’m translating:

private void Resize()
{
    Debug.Assert(IsFull);

    if (IsEmpty)
    {
        _head = new T[4];
        _capacity = 4;
        return;
    }

    _tail.Add(_head);
    int nextCapacity = _capacity == 4 ? 4 : HeadCapacity * 2;

    _head = new T[nextCapacity];
    _headCount = 0;
    _capacity += nextCapacity;
}

Here’s the pseudocode, which I translated almost verbatim:

The pseudocode seems very unnatural/imperative to me, compared to the pseudocode I read in other academic paper describing data structures. Am I doing something wrong, or can I improve on anything?

I am at the late stage of a PhD program. For some personal reasons, I have decided to quit this program and apply for a new PhD program in a different country.

I have presented one part of my research in an international conference, and I am about to submit it to a journal. Beside this paper, I have prepared 3 other papers but I have not presented them anywhere. I am the sole author of these three un-published works.

Now my question is whether it is possible to bring these researches to the next university and publish them afterwards? I am the legal owner of these researches? copyright-wise I mean.

I would be more than glad if anyone helps me in this tough situation.

PS: I would have no problem for getting recommendation letters.

I have done my own research independently from any academic institution. The theses are mainly biochemical, and aquaculture. I would like to have the work peer reviewed.

I tried to use researchgate.net but they have created a barrier to entry for autodidacts, and non-institutional researchers. The question answer format for stackexchage is also unsuitable.

Are there other web-portals specifically for independent, non-institutional, autodidact researchers?