{"id":"W7068375853","doi":"","title":"LGS 20131012 IM","year":2013,"lang":"fr","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Term (time); Context (archaeology); The Internet","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001058675,0.001258728,0.001132732,0.00287201,0.002508858,0.007501345,0.001676562,0.001915165,0.8589641],"category_scores_gemma":[0.002009125,0.0005968866,0.000624378,0.002826708,0.0008502193,0.001733429,0.002396428,0.001382597,0.833599],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006364484,"about_ca_system_score_gemma":0.004761475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1009433,"about_ca_topic_score_gemma":0.1577372,"domain_scores_codex":[0.9992871,0.00006438408,0.00003545748,0.0001195965,0.0003610608,0.0001324378],"domain_scores_gemma":[0.9981498,0.00009239107,0.00006598467,0.0002540981,0.0009603657,0.0004773486],"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":[0.00004746814,0.00001661484,0.0001398402,0.00008054845,0.000002970643,0.00003872364,0.00002010476,0.00006026187,0.0005084346,0.001093979,0.9661033,0.03188773],"study_design_scores_gemma":[0.000006908391,0.000006668427,0.0004780001,0.00003600829,0.00000141139,0.00002670953,0.00003221968,0.00005498301,0.0002057203,0.0001813096,0.9989655,0.00000455399],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001072245,0.001247534,0.002489137,0.003258485,0.002738429,0.000221375,0.06479984,0.01448804,0.909685],"genre_scores_gemma":[0.001501093,0.0003764513,0.0006913263,0.0004646461,0.0001274567,0.00004935264,0.01972276,0.001630222,0.9754367],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1410359,"threshold_uncertainty_score":0.2011706,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003485089971676244,"score_gpt":0.1824781949947474,"score_spread":0.1789931050230711,"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."}}