{"id":"W6959159932","doi":"10.7939/dvn/kcnxex/laruey","title":"trc.F90","year":2020,"lang":"en","type":"dataset","venue":"University of Alberta Library","topic":"Genetic and Environmental Crop Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000006950651,0.0001199818,0.0001946691,0.000005932972,0.0001000059,0.00000800854,0.0003942264,0.0001136485,0.006321256],"category_scores_gemma":[0.000003964399,0.00005638715,0.0001057005,0.00008601718,0.0001164468,0.00008423024,0.0004419787,0.00009739555,0.0006700234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000408984,"about_ca_system_score_gemma":0.000005165549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002335635,"about_ca_topic_score_gemma":0.0007917879,"domain_scores_codex":[0.9995009,0.00002431847,0.00006721545,0.0002027084,0.00009590862,0.0001090016],"domain_scores_gemma":[0.9997159,0.00008315522,0.00007432499,0.0000497269,0.000002005212,0.00007487846],"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":[0.00002185689,0.00003133558,0.0003547363,0.00001538127,0.00002796778,0.000009330986,0.00005916525,3.031371e-7,0.00007297347,0.000002834253,0.998722,0.0006820962],"study_design_scores_gemma":[0.00005678307,0.000124943,0.01035668,0.00001354906,0.00003511524,7.222834e-7,0.0004904714,3.873189e-7,0.00003040992,0.00001666463,0.988747,0.0001272937],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01739058,0.0001228074,4.503657e-8,0.00244584,0.00005882518,0.00008606844,0.9765894,0.00001353857,0.003292874],"genre_scores_gemma":[0.001204786,0.001148368,0.00004008892,0.0002652783,0.0000811941,5.711461e-8,0.9932205,5.259906e-7,0.004039184],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01663109,"threshold_uncertainty_score":0.9945871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009198916527292616,"score_gpt":0.138371571462567,"score_spread":0.1291726549352743,"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."}}