{"id":"W4298376510","doi":"","title":"Machine learning: A primer","year":2017,"lang":"es","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Hermeneutics and Narrative Identity","field":"Arts and Humanities","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"","keywords":"Primer (cosmetics); Computer science; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003518234,0.0002939502,0.0003297965,0.0001129304,0.004189753,0.004437404,0.001187114,0.000129688,0.002999403],"category_scores_gemma":[0.001772172,0.0002933083,0.0002120058,0.00004194676,0.0008624144,0.0004300248,0.000692946,0.0005187112,0.0004650691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005782372,"about_ca_system_score_gemma":0.0001355449,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008038455,"about_ca_topic_score_gemma":0.01219871,"domain_scores_codex":[0.9954172,0.002898067,0.0004047882,0.0005143848,0.0003674009,0.0003981171],"domain_scores_gemma":[0.9951805,0.0005000201,0.0006420391,0.001765347,0.001717016,0.0001951177],"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":[0.00001086775,0.0004759429,0.02957393,0.00007401218,0.0001057766,0.000007603424,0.01081295,0.000001338247,0.0008506167,0.9378815,0.00124747,0.01895795],"study_design_scores_gemma":[0.0006785752,0.000001057857,0.02722189,0.0007137175,0.00006916823,0.000003314138,0.0001514789,0.003921492,0.007227185,0.002731406,0.9568652,0.0004155086],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2762998,0.001618258,0.0006293715,0.02006376,0.000447331,0.0003311587,0.0001042868,0.000141563,0.7003644],"genre_scores_gemma":[0.8040904,0.001008572,0.0003446905,0.00006544127,0.00008274388,0.00001297327,0.0000745504,0.00003875972,0.1942818],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9556177,"threshold_uncertainty_score":0.9999519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02423623105862379,"score_gpt":0.2464608821184882,"score_spread":0.2222246510598644,"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."}}