{"id":"W4393823638","doi":"10.5281/zenodo.4574249","title":"ToC2ME Velocity Model","year":2021,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Mathematics; Computer 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":[],"consensus_categories":[],"category_scores_codex":[0.0007901897,0.003971314,0.001659733,0.002969054,0.0006924681,0.002223386,0.003489373,0.002376248,0.03165701],"category_scores_gemma":[0.004471026,0.0006881387,0.002023761,0.005069769,0.0004129609,0.00172936,0.001500706,0.002510251,0.07192759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001440079,"about_ca_system_score_gemma":0.001874399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02732165,"about_ca_topic_score_gemma":0.04870709,"domain_scores_codex":[0.9990239,0.00009913929,0.0001017877,0.0003957234,0.0002369727,0.0001423792],"domain_scores_gemma":[0.9987131,0.0002302175,0.00009108635,0.0004189532,0.0004570717,0.00008959579],"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":[0.0001239016,0.0000560212,0.001265461,0.0005026798,0.0000502658,0.00004661689,0.00002328186,0.002804695,0.0003827702,0.0007789201,0.9877234,0.00624201],"study_design_scores_gemma":[0.0003938796,0.00006522897,0.00544922,0.0003138581,0.00008644559,0.0001913858,0.0001423363,0.01703132,0.002035658,0.003979843,0.9702199,0.00009109582],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005153815,0.00009340448,0.000638452,0.00006130735,0.00006457506,0.00003110309,0.9949781,0.002861979,0.0007556057],"genre_scores_gemma":[0.0009165308,0.00004259358,0.0009019922,0.00002661882,0.000008361227,0.00009525596,0.9973872,0.0001962684,0.0004251465],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03165701,"threshold_uncertainty_score":0.1059033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04392269737213553,"score_gpt":0.265927920665321,"score_spread":0.2220052232931855,"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."}}