{"id":"W1574832543","doi":"10.1016/b978-012088469-8.50123-6","title":"HOS-Miner","year":2004,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Linear subspace; Subspace topology; Outlier; Anomaly detection; Computer science; Data mining; Dimension (graph theory); Range (aeronautics); Pattern recognition (psychology); Mathematics; Algorithm; Artificial intelligence; Combinatorics; Engineering","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"],"consensus_categories":[],"category_scores_codex":[0.00009115254,0.000291193,0.0002652217,0.0001406891,0.0001374057,0.000101818,0.0008910402,0.0002707919,0.000159376],"category_scores_gemma":[0.000002327197,0.0002763919,0.000217221,0.00002232139,0.00007927774,0.00006650201,0.0002866845,0.0003543384,0.0006082337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000107835,"about_ca_system_score_gemma":0.0001312527,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.276223e-7,"about_ca_topic_score_gemma":0.000002424005,"domain_scores_codex":[0.9987141,0.000005828915,0.000302162,0.0005281908,0.0002408569,0.000208838],"domain_scores_gemma":[0.9985295,0.00001603383,0.0001871308,0.001073779,0.00008385733,0.0001097252],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[2.554096e-7,0.000002443997,1.09895e-7,0.000006134378,0.000008805258,0.00000508589,0.00001964567,2.909316e-7,0.00001600058,0.3850605,0.0001922244,0.6146885],"study_design_scores_gemma":[0.00005770692,0.00003377017,0.000002771245,0.00006721805,0.00001184822,0.00001873875,3.641774e-7,0.00002040918,0.0002286699,0.2000211,0.7992737,0.000263674],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[8.097969e-7,0.0002097303,0.03571669,0.0002563126,0.0001452338,0.0003549663,0.000006354248,0.0005867228,0.9627232],"genre_scores_gemma":[0.000580687,0.00005124571,0.02344857,0.0005837837,0.0002028505,0.00008921638,0.00000443594,0.00004235507,0.9749969],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.7990814,"threshold_uncertainty_score":0.9999688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01254754736551646,"score_gpt":0.2303639005018442,"score_spread":0.2178163531363277,"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."}}