{"id":"W6931876452","doi":"10.5683/sp2/d9yyc5","title":"Cochrane Ranche -- Cochrane -- Laser Scanning -- Metadata -- November -- 2020","year":2021,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Metadata; Laser scanning; Laser; Intersection (aeronautics); Data set","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001137746,0.001632272,0.001287535,0.00371521,0.001007363,0.002766847,0.002346884,0.001477555,0.02868873],"category_scores_gemma":[0.004684736,0.0007060731,0.0009111975,0.006797097,0.0006780796,0.001148879,0.001933288,0.001201847,0.0509197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001960038,"about_ca_system_score_gemma":0.004397486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1166048,"about_ca_topic_score_gemma":0.252113,"domain_scores_codex":[0.9987637,0.0001200623,0.0001110821,0.0003535973,0.0004400485,0.0002115637],"domain_scores_gemma":[0.9979222,0.0002990483,0.0002298207,0.0005332537,0.0008317076,0.0001839834],"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":[0.000126947,0.00002296735,0.003094641,0.0007282266,0.00004438538,0.00005850511,0.00007513488,0.0004954489,0.0004907956,0.0008560283,0.9881345,0.005872458],"study_design_scores_gemma":[0.00005159993,0.0000105565,0.009312245,0.0002232382,0.00001949313,0.00006536025,0.0001191896,0.0002472155,0.0006023684,0.0005808307,0.9887316,0.00003642942],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003250011,0.00009300104,0.0001133061,0.0000293615,0.00002096475,0.00001081838,0.9979146,0.0004350845,0.001057862],"genre_scores_gemma":[0.0006156047,0.00004165757,0.0003663141,0.00001697625,0.000004250965,0.0000329763,0.9982924,0.00008677383,0.0005430134],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1166048,"threshold_uncertainty_score":0.2318522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02267911581385157,"score_gpt":0.3049362307897523,"score_spread":0.2822571149759008,"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."}}