{"id":"W4398959621","doi":"10.7910/dvn/tlahpx/b560n1","title":"ddAle_Ott_20140515_08099500.mat","year":2020,"lang":"fr","type":"dataset","venue":"Harvard Dataverse","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Computer science","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":[0.001227295,0.002804028,0.002092393,0.005659082,0.001184219,0.004719968,0.003439043,0.002739027,0.3525465],"category_scores_gemma":[0.009749883,0.001029456,0.001431638,0.009072609,0.0007371212,0.002786506,0.003081638,0.001890521,0.3803762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002356643,"about_ca_system_score_gemma":0.002776539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04077807,"about_ca_topic_score_gemma":0.0513947,"domain_scores_codex":[0.9987375,0.0001937019,0.0001187995,0.0004020943,0.0002545748,0.0002933169],"domain_scores_gemma":[0.9965218,0.0009944354,0.0003570949,0.0008116404,0.0009152388,0.0003998537],"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":[0.00002545694,0.000003923401,0.0001654182,0.0002749921,0.00001122045,0.000004983806,0.000008441998,0.00008017562,0.00002608047,0.0003466319,0.9984139,0.0006387355],"study_design_scores_gemma":[0.0001793781,0.00001143822,0.00147799,0.0003142151,0.00001952591,0.00002177158,0.00005049512,0.0001910477,0.0001727528,0.001558678,0.9959713,0.00003157238],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002152356,0.00003922879,0.00002028944,0.00006290272,0.00002235822,0.000002307795,0.9989139,0.0002934389,0.0006240984],"genre_scores_gemma":[0.0002717944,0.00006641159,0.0001184884,0.00008339554,0.00001806152,0.00003315503,0.9979256,0.0002389822,0.001243996],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6474535,"threshold_uncertainty_score":0.9235139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02435040320303037,"score_gpt":0.2496656139443467,"score_spread":0.2253152107413163,"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."}}