{"id":"W4240505264","doi":"10.1002/9780470575758.index","title":"Index","year":2010,"lang":"en","type":"paratext","venue":"","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Index (typography); Computer science; Library science; Citation; Citation index; Information retrieval; World Wide Web","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004889901,0.001603983,0.001436262,0.00362893,0.001247108,0.004296741,0.001453939,0.001460062,0.68912],"category_scores_gemma":[0.004182955,0.0003458406,0.0004515228,0.004495513,0.0005879323,0.003271623,0.001737576,0.001291313,0.674601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001038347,"about_ca_system_score_gemma":0.001157354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002361073,"about_ca_topic_score_gemma":0.003689829,"domain_scores_codex":[0.9994,0.00007801824,0.0000356042,0.0001152698,0.0003275269,0.00004355732],"domain_scores_gemma":[0.9980965,0.0004551447,0.00008180136,0.0002932861,0.0007818179,0.0002913605],"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":[0.00003697511,0.00004824874,0.0001000438,0.0002535393,0.000007594832,0.00002550989,0.00001894874,0.0003646251,0.0009067236,0.006233015,0.7842817,0.2077231],"study_design_scores_gemma":[0.00001344291,0.00002368712,0.0002586057,0.0001558683,0.00001094297,0.00006129053,0.00002448533,0.001811807,0.0009103265,0.008803028,0.9879127,0.00001376812],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00136522,0.003979755,0.03719008,0.00252182,0.008304726,0.0004163711,0.01600944,0.007429313,0.9227833],"genre_scores_gemma":[0.003662686,0.00246402,0.006788577,0.0005755212,0.001664935,0.0001739244,0.008419801,0.001303818,0.9749469],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.31088,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01315916952510883,"score_gpt":0.281235549745157,"score_spread":0.2680763802200482,"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."}}