{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004985445,0.0002847459,0.0002280683,0.002255572,0.0005745121,0.001881116,0.0003422419,0.0004077985,0.0009874391],"category_scores_gemma":[0.05006865,0.0001829375,0.0002077034,0.001388414,0.0009973015,0.001340105,0.001488534,0.0004884052,0.0001819165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008652177,"about_ca_system_score_gemma":0.0005510931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003931381,"about_ca_topic_score_gemma":0.003731075,"domain_scores_codex":[0.9958443,0.001840441,0.0003534364,0.0004036601,0.001105644,0.0004524488],"domain_scores_gemma":[0.9612285,0.02268647,0.008511976,0.001331838,0.004029214,0.002211861],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007533559,0.00008185061,0.9630758,0.00003171398,0.00003228804,0.00007552725,0.01988444,0.0002585029,0.001033713,0.0003731062,0.0003265179,0.01475123],"study_design_scores_gemma":[0.00001541042,0.0001380667,0.9557682,0.00002918922,0.00001837756,0.0001406996,0.0386282,0.002307388,0.0005928044,0.001002789,0.001327313,0.00003155746],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980955,0.00003725688,0.0008125058,0.00008908291,0.000001985243,0.00001095809,0.00002415075,0.000005767012,0.0009227835],"genre_scores_gemma":[0.9995415,0.00002971511,0.0002627668,0.00001754153,0.000002247585,0.00001046456,0.00003197911,0.000002496489,0.0001012754],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004985445,"threshold_uncertainty_score":0.02636588,"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."}}