{"id":"W2946059286","doi":"10.1007/978-3-030-20351-1_4","title":"Analyzing Brain Morphology on the Bag-of-Features Manifold","year":2019,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Jaccard index; Computer science; Pattern recognition (psychology); Artificial intelligence; Pairwise comparison; Probabilistic logic","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0004874177,0.0005876962,0.0008612571,0.001077248,0.0002962295,0.0008987226,0.0009917581,0.0006056562,0.001778004],"category_scores_gemma":[0.001899217,0.0003276308,0.0007861827,0.001207487,0.0006214675,0.001955777,0.001311391,0.001014616,0.0007898762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003757945,"about_ca_system_score_gemma":0.0003368028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001935943,"about_ca_topic_score_gemma":0.002537274,"domain_scores_codex":[0.9997078,0.0000730331,0.00001385697,0.00009103525,0.00008126511,0.00003309601],"domain_scores_gemma":[0.9993588,0.000250461,0.00008996393,0.0001404538,0.0001183537,0.00004199678],"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":[0.0001695004,0.0001058021,0.004247847,0.0001851781,0.0001815548,0.0001851594,0.000246038,0.144356,0.03148461,0.03874635,0.009998806,0.7700931],"study_design_scores_gemma":[0.000004560133,0.00005264294,0.002815568,0.000008546727,0.00001416786,0.00009116031,0.00003532888,0.9482719,0.0020762,0.04535482,0.001261184,0.00001394956],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06447721,0.000599887,0.9322801,0.0002408383,0.00004484032,0.00002224998,0.0002225413,0.001046072,0.001066187],"genre_scores_gemma":[0.669386,0.001052882,0.3207158,0.0001198691,0.0002441468,0.0000826925,0.001489249,0.00055493,0.006354279],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001935943,"threshold_uncertainty_score":0.005948007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009661325543606962,"score_gpt":0.2260191258806706,"score_spread":0.2163578003370636,"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."}}