{"id":"W3107330311","doi":"10.1007/s10489-020-02108-1","title":"Improving cluster recovery with feature rescaling factors","year":2021,"lang":"en","type":"article","venue":"Applied Intelligence","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Cluster analysis; Normalization (sociology); Computer science; Data mining; Preprocessor; Feature (linguistics); Artificial intelligence; Pattern recognition (psychology); Data pre-processing; Machine learning","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":[0.000216286,0.0002343719,0.0002222756,0.00009919641,0.0002051397,0.0003239356,0.001007468,0.0001108077,0.00002443539],"category_scores_gemma":[0.0001067649,0.0001946536,0.00005442686,0.0008731091,0.00008057587,0.0006012007,0.0008052512,0.0005274646,0.00007670739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001256619,"about_ca_system_score_gemma":0.0001821001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002123172,"about_ca_topic_score_gemma":0.00001414509,"domain_scores_codex":[0.9978024,0.00004269115,0.0002134927,0.0008266573,0.0005356722,0.0005791044],"domain_scores_gemma":[0.9982721,0.0002945025,0.00008793604,0.0009915616,0.0001920275,0.0001618573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008329086,0.00009998617,0.0001533615,0.0001183509,0.00007042121,0.0002372133,0.001509799,0.02868092,0.02135261,0.02053387,0.0002835779,0.9268766],"study_design_scores_gemma":[0.0002794348,0.0002018477,0.0002779166,0.000130781,0.00001170827,0.0001730169,0.001092589,0.2061855,0.7785538,0.007684405,0.004430748,0.0009782773],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004384256,0.0001424039,0.9911299,0.0003839417,0.0002020648,0.0001802621,0.000001718303,0.0002202502,0.003355196],"genre_scores_gemma":[0.3647135,0.00005442895,0.6320445,0.0006433245,0.0001125887,0.00004596738,0.000009252081,0.00004520203,0.002331179],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9258983,"threshold_uncertainty_score":0.7937744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0182613382848832,"score_gpt":0.2635628413197893,"score_spread":0.2453015030349061,"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."}}