{"id":"W7009955722","doi":"","title":"Fondations of Machine Learning, part 1","year":2019,"lang":"en","type":"other","venue":"OpenEdition (OpenEdition)","topic":"Gaussian Processes and Bayesian Inference","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Centre National de la Recherche Scientifique; AXA Research Fund","keywords":"Model selection; Selection (genetic algorithm); Series (stratigraphy); Econometric model; Maximum likelihood; Time series","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00213336,0.001052286,0.0007872724,0.002554433,0.001850146,0.007364135,0.001138289,0.002679547,0.1513397],"category_scores_gemma":[0.008271188,0.0004141329,0.0005687914,0.002482434,0.002961891,0.005295911,0.002327246,0.004984218,0.06085504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003398618,"about_ca_system_score_gemma":0.001922612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001777462,"about_ca_topic_score_gemma":0.003060461,"domain_scores_codex":[0.9978805,0.0004878068,0.0001141101,0.0004473364,0.0009271833,0.000143177],"domain_scores_gemma":[0.9967983,0.001238541,0.0002010082,0.0005919353,0.0008754044,0.0002947458],"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":[0.00001861091,0.00002483753,0.0002068289,0.0001424042,0.000009755174,0.00003090364,0.00009039876,0.0002084249,0.0001164698,0.2142654,0.6537424,0.1311436],"study_design_scores_gemma":[0.000002205041,0.000009476771,0.0002858487,0.0001867802,0.000002372252,0.00007212508,0.00003791934,0.0003282946,0.0001056184,0.06237318,0.9365879,0.00000834364],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001010693,0.08762003,0.0273274,0.07175757,0.04599851,0.00007372004,0.001353963,0.001018648,0.7638395],"genre_scores_gemma":[0.01801661,0.03994429,0.009641686,0.008318406,0.03258195,0.0001579135,0.00116153,0.0009554095,0.8892221],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1513397,"threshold_uncertainty_score":0.5062817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01324343665382424,"score_gpt":0.2360545800031397,"score_spread":0.2228111433493155,"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."}}