{"id":"W3134611889","doi":"10.17504/protocols.io.smeec3e","title":"Serum Biochemical Indexes Detection v1","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Computational biology; Biology","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":[0.002164744,0.002306367,0.001600962,0.002570643,0.001053813,0.001372185,0.001143977,0.001744995,0.02486682],"category_scores_gemma":[0.004026748,0.0009360112,0.001282396,0.001495358,0.0008450659,0.0008860471,0.001496219,0.003068445,0.02362801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004220639,"about_ca_system_score_gemma":0.001401992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005684497,"about_ca_topic_score_gemma":0.000580134,"domain_scores_codex":[0.9963014,0.0007369136,0.0004918099,0.0009932903,0.001169254,0.0003072332],"domain_scores_gemma":[0.9982269,0.0002996321,0.0001308832,0.0005485605,0.0006507452,0.0001431285],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003638042,0.0006049308,0.007358203,0.001486828,0.0002242541,0.000952978,0.0005180957,0.0005736405,0.8034552,0.008900718,0.03778146,0.1345056],"study_design_scores_gemma":[0.0003289329,0.00189241,0.01841613,0.0003675891,0.0002641144,0.0033324,0.0001302624,0.003817166,0.7441736,0.006331393,0.2207102,0.0002358125],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08973834,0.007120645,0.7684693,0.001295468,0.002783042,0.01772008,0.03377128,0.02441042,0.05469147],"genre_scores_gemma":[0.1710462,0.004697245,0.6203617,0.003466079,0.001003653,0.04163577,0.06442167,0.005601902,0.08776573],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02486682,"threshold_uncertainty_score":0.08318782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01096918416861832,"score_gpt":0.2533247747405911,"score_spread":0.2423555905719728,"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."}}