{"id":"W6894197575","doi":"10.5281/zenodo.7574598","title":"jnsheff/CanadaTM: v2.0","year":2023,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Construct (python library); Set (abstract data type); Scripting language; Term (time); Data set","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002166902,0.003408089,0.002551829,0.007596744,0.003256122,0.005843104,0.006248166,0.001867274,0.2675919],"category_scores_gemma":[0.01090737,0.002643325,0.002134056,0.01339061,0.001044054,0.003667947,0.004674687,0.003468949,0.3812298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005131837,"about_ca_system_score_gemma":0.01715674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4378026,"about_ca_topic_score_gemma":0.5843917,"domain_scores_codex":[0.9978579,0.0001966617,0.0001631266,0.0006604875,0.0006587576,0.000463171],"domain_scores_gemma":[0.9941615,0.0008043941,0.0002489606,0.001586701,0.002688115,0.0005102419],"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":[0.00003935632,0.000006332046,0.0003137605,0.0002025585,0.00001963975,0.000009560248,0.00003677895,0.00009726802,0.0001520953,0.0003355113,0.9968662,0.001921104],"study_design_scores_gemma":[0.00008189413,0.000005581811,0.001762997,0.0001564512,0.00002797682,0.00003570733,0.00008097694,0.0003649644,0.0008264849,0.001362715,0.9952227,0.00007149585],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.0001510397,0.00006354447,0.0009321854,0.00008406664,0.00005525627,0.00004328614,0.9776766,0.01774491,0.00324911],"genre_scores_gemma":[0.0004768269,0.00007390903,0.002399019,0.0001302412,0.00001483983,0.0002181215,0.981445,0.01156823,0.003673801],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.4378026,"threshold_uncertainty_score":0.895184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04056476947743064,"score_gpt":0.2517371251702739,"score_spread":0.2111723556928433,"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."}}