{"id":"W4394053924","doi":"10.5281/zenodo.883812","title":"Empirical Data From A Longitudinal Software Maintenance Experiment","year":2017,"lang":"en","type":"dataset","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Software Reliability and Analysis Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Software; Longitudinal data; Empirical research; Computer science; Statistics; Data mining; Mathematics; Programming language","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.001845256,0.0009413505,0.001318282,0.0006545027,0.0008851779,0.002242972,0.01879745,0.001061485,0.0002301731],"category_scores_gemma":[0.003394789,0.0008715632,0.0004794503,0.0006327239,0.0004090839,0.0013974,0.01101387,0.001981904,0.0005415799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009516264,"about_ca_system_score_gemma":0.001541733,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05061874,"about_ca_topic_score_gemma":0.01075069,"domain_scores_codex":[0.9921286,0.0004900837,0.0009960992,0.002936753,0.001816477,0.001632008],"domain_scores_gemma":[0.97991,0.0008251047,0.0007442635,0.0173628,0.0003337123,0.0008241897],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004045543,0.0004717486,0.004909831,0.00006358171,0.000219863,0.0005685777,0.00003151334,0.00005775727,0.00001625122,0.0000502852,0.9878287,0.005741468],"study_design_scores_gemma":[0.0004965426,0.0001470929,0.007275891,0.0003130094,0.0001190433,0.00008538244,0.00001298226,0.04490937,0.0001666844,0.001817472,0.9434852,0.001171308],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000793115,0.002163202,0.4769343,0.002514846,0.0002404857,0.0004625399,0.5171031,0.0004938464,0.000008429249],"genre_scores_gemma":[0.0005713095,0.001567464,0.1532571,0.001412591,0.0005128856,0.0005941683,0.841543,0.00006796302,0.0004735445],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3244399,"threshold_uncertainty_score":0.9993735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05726297677289785,"score_gpt":0.3437017101189482,"score_spread":0.2864387333460504,"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."}}