{"id":"W6955331845","doi":"10.58079/oq7w","title":"Mercredi 16 juin : Catherine Ferland et Benoît Grenier, de l'univ. de Sherbrooke","year":2010,"lang":"fr","type":"article","venue":"OpenEdition (OpenEdition)","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Theme (computing); Event (particle 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001399096,0.0006058113,0.0004609638,0.000139772,0.000443942,0.00036011,0.0007907809,0.0009469967,0.006882957],"category_scores_gemma":[0.0005866461,0.0006738545,0.0002652554,0.0002574075,0.0004174637,0.0005608514,0.000408764,0.00122907,0.0007220285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002231497,"about_ca_system_score_gemma":0.0007077301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005682841,"about_ca_topic_score_gemma":0.01163181,"domain_scores_codex":[0.9967623,0.0003799265,0.0007679249,0.0006473506,0.0004596392,0.0009828082],"domain_scores_gemma":[0.9975851,0.0001020429,0.0004043994,0.0009785392,0.000345856,0.000584037],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009023481,0.002011564,0.01002072,0.001479997,0.000858473,0.0001828248,0.001202723,0.003148334,0.3710766,0.1879911,0.3590182,0.06210711],"study_design_scores_gemma":[0.002087393,0.0007228178,0.01670305,0.0002123404,0.0001726655,0.0006361529,0.0001578713,0.002676302,0.03944801,0.001385963,0.9348559,0.0009415621],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5931038,0.005550541,0.04839556,0.1421713,0.01244388,0.002104689,0.002256599,0.0002862617,0.1936874],"genre_scores_gemma":[0.8436489,0.003375905,0.034131,0.04511059,0.004804346,0.0003340384,0.009883768,0.0002380654,0.05847342],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5758377,"threshold_uncertainty_score":0.9995713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007197924844726568,"score_gpt":0.2513801016192935,"score_spread":0.244182176774567,"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."}}