{"id":"W2773989484","doi":"10.1109/esem.2017.17","title":"Characterizing Software Developers by Perceptions of Productivity","year":2017,"lang":"en","type":"article","venue":"","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Productivity; Computer science; Software; Perception; Work (physics); Software engineering; Knowledge management; Data science; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009296692,0.00006586842,0.0001265242,0.00009467184,0.0004309397,0.0003585728,0.000744107,0.00002518548,0.001514858],"category_scores_gemma":[0.0009918232,0.00004677539,0.00005620857,0.00008664488,0.0001054443,0.001766171,0.0001846854,0.00004697955,0.0003936933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001171172,"about_ca_system_score_gemma":0.00002245706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003664459,"about_ca_topic_score_gemma":0.00002091742,"domain_scores_codex":[0.9988385,0.00002041939,0.0002871758,0.0001716775,0.0005711595,0.0001110141],"domain_scores_gemma":[0.9988434,0.00004749861,0.0002639729,0.0005927791,0.0002079385,0.00004443248],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001145833,0.0000671419,0.7274176,0.000006144333,0.00001033653,5.103212e-7,0.00144988,0.000001228065,0.01523487,0.0006190051,0.06424538,0.1909364],"study_design_scores_gemma":[0.00009437451,0.000009389235,0.9594474,0.00000408967,0.000004823293,5.544099e-7,0.001018802,0.00004105334,0.0018512,0.0001478427,0.03729545,0.00008501647],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9822565,0.00000255411,0.004425487,0.001852659,0.0001657996,0.0001001394,0.0000231357,0.00002873308,0.01114502],"genre_scores_gemma":[0.9762719,0.000002796802,0.002575722,0.0001240721,0.00002151754,0.000006269285,0.000006750665,0.000002911024,0.02098801],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2320298,"threshold_uncertainty_score":0.9993979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2543324859706995,"score_gpt":0.4379287447779625,"score_spread":0.183596258807263,"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."}}