{"id":"W6942951480","doi":"10.15454/hnxeod/qdgrzw","title":"VR2AR-546350.txt","year":2020,"lang":"en","type":"dataset","venue":"Recherche Data Gouv France","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Fisheries and Oceans Canada; Ocean Tracking Network","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":["metaresearch","metaepi_narrow","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"category_scores_codex":[0.005229897,0.001410379,0.001683061,0.0002867496,0.0001984213,0.0003376855,0.01321977,0.00306514,0.003633028],"category_scores_gemma":[0.01339921,0.00148151,0.0002270581,0.00247141,0.0003805695,0.001023212,0.004587131,0.00834167,0.396749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007837333,"about_ca_system_score_gemma":0.001255735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001636985,"about_ca_topic_score_gemma":0.0006111258,"domain_scores_codex":[0.9899064,0.002681276,0.00118451,0.003413116,0.001479567,0.001335126],"domain_scores_gemma":[0.9833793,0.001763095,0.0009398413,0.0130395,0.0002234269,0.0006548617],"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":[0.00009503826,0.000197921,0.000009676149,0.000645111,0.0003091898,0.0002243637,0.00003737145,0.000003017921,0.0002107418,0.000004930384,0.9945154,0.003747216],"study_design_scores_gemma":[0.0007353062,0.0000645191,0.00005363689,0.0004043473,0.0004047552,0.00004261896,0.00002185171,0.0001939077,0.0001007923,0.0001446158,0.9962741,0.001559522],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000002607143,0.00214646,0.000157961,0.0005778241,0.001211216,0.0009792348,0.9937118,0.0006547245,0.0005581685],"genre_scores_gemma":[5.742815e-7,0.003912474,0.009324592,0.002194802,0.002192626,0.0001150964,0.9805549,0.0004439421,0.00126097],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3931159,"threshold_uncertainty_score":0.9998646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5534134553383777,"score_gpt":0.4553897591362248,"score_spread":0.0980236962021529,"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."}}