{"id":"W4398427745","doi":"10.7910/dvn/itvlik/hcco5b","title":"pre-merge-commit.sample","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Commit; Merge (version control); Computer science; Database; Parallel computing","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001685518,0.003475374,0.001287309,0.003567974,0.00168448,0.003181698,0.003261744,0.00239717,0.131911],"category_scores_gemma":[0.01136708,0.001104005,0.001676931,0.005506772,0.0006934237,0.003016204,0.002897116,0.001875978,0.1413524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001495613,"about_ca_system_score_gemma":0.003057014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01382846,"about_ca_topic_score_gemma":0.02899176,"domain_scores_codex":[0.9978537,0.0002344818,0.000227634,0.0007490334,0.0005141192,0.0004209554],"domain_scores_gemma":[0.9946383,0.001065871,0.0001827257,0.002524894,0.001163911,0.0004243483],"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":[0.0001156361,0.00002973987,0.0004604741,0.0002692291,0.00001990917,0.00001472639,0.00002474473,0.0001631127,0.000247658,0.0004118656,0.9951009,0.003142013],"study_design_scores_gemma":[0.0009112243,0.00007108031,0.003254814,0.000216653,0.00003369066,0.00009864544,0.0001606097,0.001910862,0.004330844,0.004817114,0.9841459,0.00004863083],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0007305129,0.00009312351,0.0005332245,0.0001807955,0.0001505552,0.00006309855,0.9819506,0.01323517,0.003063002],"genre_scores_gemma":[0.001452803,0.00005417798,0.002256622,0.0001344508,0.00002634757,0.0001726047,0.9920596,0.002523975,0.00131944],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.868089,"threshold_uncertainty_score":0.4412863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02492523784114841,"score_gpt":0.2811614299723452,"score_spread":0.2562361921311968,"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."}}