{"id":"W2192128789","doi":"10.1016/j.infsof.2015.10.002","title":"Understanding the popular users: Following, affiliation influence and leadership on GitHub","year":2015,"lang":"en","type":"article","venue":"Information and Software Technology","topic":"Open Source Software Innovations","field":"Computer Science","cited_by":110,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Popularity; Computer science; Context (archaeology); World Wide Web; Feature (linguistics); Internet privacy; Data science; Psychology; Social psychology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.001403787,0.0001293768,0.0001776294,0.001699261,0.001628481,0.004371301,0.0006840928,0.0007629298,0.0127981],"category_scores_gemma":[0.01124318,0.0001684801,0.0001657575,0.002184498,0.001446858,0.003838711,0.002049348,0.0009878479,0.001533133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001634621,"about_ca_system_score_gemma":0.001332952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03175507,"about_ca_topic_score_gemma":0.06389613,"domain_scores_codex":[0.9989242,0.0004034488,0.00003428867,0.00009513782,0.0002649376,0.0002779138],"domain_scores_gemma":[0.9875168,0.004814324,0.002660643,0.0005714449,0.001836528,0.002600173],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003285543,0.0003551228,0.9019154,0.00005662653,0.00004215694,0.0002314004,0.0460158,0.0002271692,0.001096779,0.007608459,0.004583056,0.03753953],"study_design_scores_gemma":[0.00001277806,0.00008066276,0.8991994,0.00004868204,0.00003062699,0.0001099409,0.08672688,0.00185909,0.0005504619,0.003097875,0.00825143,0.00003215177],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9778705,0.00006423907,0.0002412189,0.0009990488,0.000009636361,0.000007572117,0.00008973604,0.00001925717,0.02069875],"genre_scores_gemma":[0.998111,0.00004406398,0.00009110968,0.00008973001,0.00001090816,0.000004169577,0.00006355872,0.00002398387,0.001561373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9983007,"threshold_uncertainty_score":0.06314051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1301124145003833,"score_gpt":0.2697044828517608,"score_spread":0.1395920683513775,"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."}}