{"id":"W4298864566","doi":"","title":"Predictive biology for heath and resilience","year":2018,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Adipose Tissue and Metabolism","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Resilience (materials science); Computer science; Physics","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":[0.002204757,0.0006684143,0.0006413984,0.0008970167,0.0007584908,0.002499162,0.0008117275,0.001114024,0.00729517],"category_scores_gemma":[0.00477014,0.0003727693,0.000715557,0.0006128474,0.002532047,0.001667701,0.00158491,0.001683255,0.0006208461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001288567,"about_ca_system_score_gemma":0.001283174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005173259,"about_ca_topic_score_gemma":0.002934458,"domain_scores_codex":[0.9993755,0.0001762849,0.00001793422,0.0002280542,0.00009689161,0.000105261],"domain_scores_gemma":[0.9980872,0.0008919091,0.000296869,0.00026971,0.0002060627,0.0002482449],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001359692,0.0005298431,0.2120697,0.001029135,0.001131369,0.001255193,0.002942955,0.05595866,0.146747,0.2656108,0.01069906,0.3006665],"study_design_scores_gemma":[0.0001244708,0.0007625591,0.4051375,0.0005083219,0.0004518099,0.0006735288,0.003291013,0.1129151,0.02128868,0.4248345,0.02970849,0.0003040891],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7755553,0.01072742,0.164175,0.01793674,0.0008823281,0.0001559438,0.001806236,0.0008764041,0.02788471],"genre_scores_gemma":[0.9875777,0.001670952,0.006128965,0.0007191384,0.0002455923,0.00007142797,0.0003473106,0.00005432554,0.003184702],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00729517,"threshold_uncertainty_score":0.02440476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01741063681996631,"score_gpt":0.2759979684185466,"score_spread":0.2585873315985803,"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."}}