{"id":"W3202653164","doi":"10.18280/ts.380425","title":"An Efficient Image Based Feature Extraction and Feature Selection Model for Medical Data Clustering Using Deep Neural Networks","year":2021,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Artificial intelligence; Pattern recognition (psychology); Cluster analysis; Feature selection; Artificial neural network; Feature extraction; Data mining; Feature (linguistics); Image (mathematics); Selection (genetic algorithm)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004115924,0.0001638126,0.0001308132,0.00006772571,0.0004161593,0.0002168113,0.0001941218,0.0001443411,0.00008556891],"category_scores_gemma":[0.0001395068,0.0001631259,0.00004246511,0.0002547618,0.00005933519,0.0003617593,0.00005110403,0.000317361,4.128925e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007731094,"about_ca_system_score_gemma":0.00007388921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002688496,"about_ca_topic_score_gemma":0.00006429879,"domain_scores_codex":[0.9982791,0.0001725657,0.0001933743,0.000680894,0.0004050953,0.0002689783],"domain_scores_gemma":[0.9992583,0.0001299577,0.0001089283,0.0002593116,0.00007648813,0.0001669512],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00015023,0.0001549736,0.0000267563,0.00003055073,0.00000382437,0.000009403173,0.00006190105,0.4352605,0.553444,0.00004383955,0.0001654867,0.01064848],"study_design_scores_gemma":[0.0008663514,0.00006275553,0.0004113853,0.00001749169,0.00003408729,0.0001636472,0.00006048368,0.978308,0.01976926,0.000009258056,0.0001322696,0.0001650716],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1073263,0.00002921382,0.8906688,0.00129804,0.0002333159,0.00029742,0.00002769238,0.0001017999,0.00001744042],"genre_scores_gemma":[0.9882296,0.000004607646,0.01014742,0.001113161,0.0002982761,0.00002565024,0.000120396,0.00002587417,0.00003501393],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8809034,"threshold_uncertainty_score":0.6652081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05783693060753348,"score_gpt":0.3201677201556459,"score_spread":0.2623307895481124,"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."}}