{"id":"W3091970108","doi":"10.1007/s10664-020-09851-6","title":"Publish or perish, but do not forget your software artifacts","year":2020,"lang":"en","type":"article","venue":"Empirical Software Engineering","topic":"Software Engineering Research","field":"Computer Science","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Deutsche Forschungsgemeinschaft; Deutscher Akademischer Austauschdienst","keywords":"Artifact (error); Publish or perish; Computer science; Publication; Context (archaeology); Replication (statistics); Data science; Software; Empirical research; Open science; Software engineering; World Wide Web; Publishing; Artificial intelligence; Political science","routes":{"ca_aff":true,"ca_fund":false,"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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03926472,0.0005856666,0.0008782591,0.01326257,0.00318913,0.01465719,0.001895854,0.002079788,0.03838458],"category_scores_gemma":[0.3336393,0.0005147593,0.001152808,0.02374813,0.002927776,0.01351739,0.00597175,0.002581043,0.02520091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001856831,"about_ca_system_score_gemma":0.005223542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001280714,"about_ca_topic_score_gemma":0.00212359,"domain_scores_codex":[0.9515345,0.01671341,0.005835456,0.003312386,0.02127667,0.001327583],"domain_scores_gemma":[0.5170412,0.2245535,0.06974537,0.1044062,0.07098224,0.01327153],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004285143,0.0002336832,0.07632587,0.00660626,0.0004945968,0.001108062,0.007279199,0.000638482,0.0026833,0.04430477,0.4117031,0.4481942],"study_design_scores_gemma":[0.00008438859,0.0001607789,0.02872821,0.002811592,0.000157537,0.0008668721,0.002875063,0.0005024544,0.002126779,0.03610009,0.9254823,0.0001037765],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"commentary","genre_scores_codex":[0.2510163,0.05541454,0.09041624,0.1939704,0.05408392,0.001592005,0.05169312,0.01135852,0.2904549],"genre_scores_gemma":[0.7279933,0.02974627,0.07361425,0.02142662,0.0232576,0.001048854,0.03157077,0.005664536,0.08567788],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.9607353,"threshold_uncertainty_score":0.2076542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06981769528065791,"score_gpt":0.2983438529525711,"score_spread":0.2285261576719132,"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."}}