{"id":"W2613634265","doi":"","title":"Scaling learning algorithms towards AI","year":2007,"lang":"en","type":"article","venue":"","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":930,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Artificial intelligence; Computer science; Machine learning; Kernel (algebra); Curse of dimensionality; Kernel method; Algorithm; Support vector machine; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.00103393,0.00007256208,0.0000686206,0.00008913867,0.0001497095,0.0001588397,0.0004269732,0.0000423195,0.00004157996],"category_scores_gemma":[0.0001590853,0.00006208622,0.0000293487,0.0002910499,0.00001473405,0.0003431106,0.0001323057,0.0002509651,0.0002027912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002133174,"about_ca_system_score_gemma":0.00002652639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001226719,"about_ca_topic_score_gemma":0.000005975241,"domain_scores_codex":[0.9991101,0.00003759133,0.0001540492,0.0002613638,0.0002131891,0.0002237222],"domain_scores_gemma":[0.9994458,0.00007421422,0.00004569911,0.0003006009,0.00005168159,0.00008202123],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001045772,0.0000125593,0.001397877,0.000002529993,0.000002532547,0.000004225189,0.000190144,0.0001433486,0.0003216371,0.04962149,0.0003015993,0.948001],"study_design_scores_gemma":[0.0002165352,0.00005314005,0.04451632,0.000009782725,0.000002715442,0.00002363255,0.00009484292,0.6888559,0.0042266,0.000982984,0.260782,0.0002355442],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001641163,0.00002857794,0.9483253,0.001784205,0.0001744786,0.00003058288,1.185557e-7,0.0004570741,0.04755851],"genre_scores_gemma":[0.8017285,0.000006783285,0.1932346,0.0007531186,0.0001290631,0.000001383839,0.000009617074,0.000006489879,0.004130385],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9477655,"threshold_uncertainty_score":0.2606538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01827361657636038,"score_gpt":0.3036296303033375,"score_spread":0.2853560137269771,"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."}}