{"id":"W6936195196","doi":"10.57745/cawbon","title":"list_files-V1.xls","year":2024,"lang":"en","type":"dataset","venue":"Recherche Data Gouv France","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Livestock and Meat Agency; University of Alberta","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","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":["insufficient_payload"],"category_scores_codex":[0.001823564,0.004183005,0.002722408,0.005633371,0.001678666,0.005147695,0.00431978,0.004162109,0.3650678],"category_scores_gemma":[0.0132175,0.001430922,0.002043048,0.008855336,0.0008990737,0.003551927,0.003199304,0.002565824,0.3714654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002463154,"about_ca_system_score_gemma":0.003655303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03435539,"about_ca_topic_score_gemma":0.04381486,"domain_scores_codex":[0.9981838,0.0003491043,0.0002002928,0.0005928054,0.0003586136,0.0003153742],"domain_scores_gemma":[0.9944419,0.002200047,0.0003102024,0.001230433,0.001369924,0.0004473936],"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":[0.00004572691,0.00001556014,0.0001825507,0.0005310604,0.00001916555,0.00001019916,0.00001696965,0.000109098,0.0000606109,0.0002799633,0.9977337,0.0009953766],"study_design_scores_gemma":[0.0003879002,0.00002395729,0.001522099,0.0003376404,0.00002611709,0.00004407622,0.00009355976,0.0002672225,0.0004339228,0.001446094,0.9953689,0.00004855432],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003741089,0.00003423163,0.00004117181,0.0000606399,0.00002376213,0.00001027868,0.9986425,0.0005772135,0.0005727012],"genre_scores_gemma":[0.0002056782,0.00004213407,0.0002699147,0.00006640009,0.00001261057,0.00009318285,0.9980031,0.0003691625,0.0009378973],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6349322,"threshold_uncertainty_score":0.9056537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3882545356586814,"score_gpt":0.4536175567369155,"score_spread":0.06536302107823405,"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."}}