{"id":"W2772747611","doi":"10.1038/nmeth.4526","title":"Machine learning: a primer","year":2017,"lang":"es","type":"article","venue":"Nature Methods","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":241,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"National Institute of Mental Health","keywords":"Primer (cosmetics); Computational biology; Computer science; Biology; Artificial intelligence; Chemistry","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":[0.005000621,0.001511394,0.001739417,0.00347678,0.0007516902,0.00478225,0.003446513,0.005130775,0.008953317],"category_scores_gemma":[0.008336027,0.001109428,0.001269259,0.002861856,0.005280633,0.009917541,0.003025472,0.010245,0.009081651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001407507,"about_ca_system_score_gemma":0.001681354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006556229,"about_ca_topic_score_gemma":0.000878841,"domain_scores_codex":[0.9974184,0.001293063,0.0002228834,0.0003122488,0.0006848634,0.00006840898],"domain_scores_gemma":[0.9899595,0.007952446,0.0002959393,0.0006816415,0.0008652132,0.0002451407],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002833537,0.0001303052,0.0003800762,0.001752179,0.00006425229,0.000102369,0.0001793356,0.002725568,0.0004690783,0.4639476,0.2601031,0.2701178],"study_design_scores_gemma":[0.00001328567,0.00003065441,0.0003230356,0.001022029,0.00001461123,0.0002957807,0.00005748841,0.004401844,0.0003205449,0.4343572,0.5591335,0.0000301924],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0005160238,0.4010341,0.4646968,0.06763075,0.01486711,0.0001101525,0.0004049575,0.0008835891,0.04985664],"genre_scores_gemma":[0.02406398,0.4390756,0.333988,0.05630016,0.07262015,0.001504815,0.0009835997,0.001381323,0.07008231],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008953317,"threshold_uncertainty_score":0.02995181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03465492183432028,"score_gpt":0.4239045969834016,"score_spread":0.3892496751490813,"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."}}