{"id":"W6960309858","doi":"10.1371/journal.pone.0033837.t001","title":"Resources utilization for JIT Service (2006 Canadian dollars).","year":2015,"lang":"en","type":"dataset","venue":"Figshare","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Service (business); Production (economics); Amortized analysis","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":[0.0012656,0.001807655,0.00136348,0.005958182,0.001370151,0.003013061,0.002980738,0.001273188,0.1001894],"category_scores_gemma":[0.01165232,0.0007158444,0.001368896,0.01717333,0.0004059953,0.00117834,0.001335181,0.002021502,0.04158669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01366882,"about_ca_system_score_gemma":0.02577874,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8993738,"about_ca_topic_score_gemma":0.9393101,"domain_scores_codex":[0.9986874,0.0001113817,0.0001201917,0.0003113536,0.0004632669,0.0003062965],"domain_scores_gemma":[0.9943982,0.0008563614,0.0005216702,0.0005591294,0.003052848,0.0006118345],"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":[0.00001865596,0.000005559612,0.001167814,0.0003058605,0.00002033185,0.000006950158,0.00001205378,0.0002702306,0.000009313814,0.0004940686,0.9958917,0.001797367],"study_design_scores_gemma":[0.000109228,0.000005993429,0.01192992,0.0004903839,0.00004290819,0.00002450068,0.00009931419,0.0006670047,0.0001115089,0.0008471934,0.9856353,0.00003669572],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004653756,0.00005461978,0.00002110654,0.00005239214,0.0000120325,0.000004020189,0.9990807,0.00005746436,0.0006711659],"genre_scores_gemma":[0.0008128892,0.0001344038,0.0002777697,0.00006139756,0.000007728772,0.00004489809,0.9971419,0.0000555595,0.00146348],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1006262,"threshold_uncertainty_score":0.3351669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06372695414015377,"score_gpt":0.2765581801038512,"score_spread":0.2128312259636975,"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."}}