{"id":"W1524539223","doi":"10.1684/vir.2013.0478","title":"A map of science based on the articles submission flows.","year":2013,"lang":"en","type":"article","venue":"PubMed","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Library science; Humanities; Political science; Art; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.001797073,0.001619165,0.001017988,0.06176977,0.001431669,0.006963268,0.0009023771,0.001177089,0.1270552],"category_scores_gemma":[0.01795372,0.0005778464,0.00157923,0.08891256,0.0005308079,0.004663195,0.002444051,0.001366638,0.04476212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001985776,"about_ca_system_score_gemma":0.007773549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01603384,"about_ca_topic_score_gemma":0.01408986,"domain_scores_codex":[0.9983464,0.0002113191,0.0002616577,0.0003333348,0.000644288,0.0002029135],"domain_scores_gemma":[0.9856221,0.005311867,0.002107211,0.0005889952,0.00553328,0.0008365291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005880732,0.0000964742,0.01284699,0.01421852,0.0003409294,0.0004898491,0.002046413,0.002338148,0.002514495,0.03821309,0.5890477,0.3372593],"study_design_scores_gemma":[0.00004928442,0.00005329343,0.01688736,0.001290889,0.000115335,0.0002073913,0.0008114816,0.0007912464,0.0004852728,0.01072156,0.9685434,0.00004352006],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.008106211,0.01126788,0.007633684,0.003396225,0.001767642,0.0005749094,0.8567736,0.00682367,0.1036563],"genre_scores_gemma":[0.08900229,0.03459803,0.1020143,0.0006345175,0.001370385,0.002560803,0.7128038,0.002264499,0.0547513],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9382302,"threshold_uncertainty_score":0.4250419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5654763445074102,"score_gpt":0.4875579879652732,"score_spread":0.07791835654213708,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}