{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003571451,0.004527899,0.00291417,0.004273805,0.001087401,0.003764557,0.003269374,0.001493189,0.09700905],"category_scores_gemma":[0.008760356,0.001737656,0.003214131,0.003479297,0.0007726486,0.001499852,0.00219951,0.003298222,0.1066931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001358972,"about_ca_system_score_gemma":0.003048046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009464617,"about_ca_topic_score_gemma":0.01555311,"domain_scores_codex":[0.9977689,0.0004317904,0.0002493571,0.0009067956,0.000444408,0.0001988659],"domain_scores_gemma":[0.9967084,0.001748436,0.000221727,0.0007842099,0.0003956626,0.0001415328],"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":[0.0003065999,0.00005721007,0.00147351,0.001801898,0.0002687348,0.00006593535,0.00007087931,0.001161179,0.001612569,0.001792036,0.9838442,0.007545229],"study_design_scores_gemma":[0.0009769601,0.00007606567,0.004311917,0.000369031,0.0002149175,0.000197352,0.00007536489,0.003755051,0.004388111,0.01104861,0.9744512,0.0001353298],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003940809,0.0001413651,0.003309579,0.0001224891,0.00005385203,0.00008087478,0.9717951,0.02303518,0.001067479],"genre_scores_gemma":[0.002143263,0.0002150945,0.0125261,0.0002641185,0.00002561149,0.0008359608,0.9733647,0.008846941,0.001778176],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09700905,"threshold_uncertainty_score":0.3245276,"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."}}