{"id":"W6924364217","doi":"10.15454/qsmrmx/yohqpe","title":"PLOTS Gene.R","year":2020,"lang":"en","type":"dataset","venue":"Recherche Data Gouv France","topic":"Reproductive Health and Technologies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Nautical Research Society","funders":"","keywords":"Expression (computer science); Gene expression; Pipeline (software); Process (computing); Workflow","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","research_integrity","insufficient_payload"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.001201007,0.0004260376,0.0008893245,0.000135083,0.00007646449,0.00002880486,0.001747594,0.001477097,0.0001316854],"category_scores_gemma":[0.01103914,0.0003704529,0.00007861912,0.0006952625,0.0001959097,0.0001533067,0.00100156,0.00362364,0.00321977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001941214,"about_ca_system_score_gemma":0.0008795806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000297051,"about_ca_topic_score_gemma":0.00001691451,"domain_scores_codex":[0.9967337,0.0002430619,0.0004857256,0.001587701,0.0004433931,0.0005064694],"domain_scores_gemma":[0.9930205,0.000306138,0.0002598512,0.006018235,0.0001350931,0.000260155],"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":[0.00009500336,0.0001020494,0.00005698173,0.001229842,0.00009990819,0.000177473,0.00000781084,9.405477e-8,0.0001218801,0.000004074652,0.9823241,0.01578073],"study_design_scores_gemma":[0.0004771161,0.0001763692,0.0003997199,0.0002549607,0.0001716462,0.0000924432,0.00001328998,0.00001161354,0.0006481332,0.0001702477,0.9972709,0.0003135759],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003882288,0.006868433,0.0001025008,0.006741722,0.0005309651,0.0008420689,0.9843346,0.0003819197,0.0001589786],"genre_scores_gemma":[0.00000320785,0.01894593,0.01307795,0.003044377,0.001199547,0.0000657603,0.9630762,0.00005042424,0.0005365545],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02125835,"threshold_uncertainty_score":0.9998748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5254136818318038,"score_gpt":0.4721650212381894,"score_spread":0.05324866059361444,"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."}}