{"id":"W4316463982","doi":"10.18280/ts.390634","title":"Detection of Breast Cancer Using Modified Markov Model","year":2022,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Closeness; Cluster analysis; Exploit; Computer science; Segmentation; Maxima and minima; Process (computing); Markov chain; Variable (mathematics); Algorithm; Artificial intelligence; Pattern recognition (psychology); Data mining; Mathematics; Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004662119,0.0003752616,0.0006714035,0.0007898915,0.0002889046,0.0006184811,0.0009599919,0.0007379586,0.001297577],"category_scores_gemma":[0.0011843,0.0003579757,0.001187691,0.0005501303,0.0003805878,0.0005564956,0.0005866491,0.0006279908,0.0004480106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007053151,"about_ca_system_score_gemma":0.0007958729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006766479,"about_ca_topic_score_gemma":0.005571383,"domain_scores_codex":[0.9996321,0.00007810359,0.00001735457,0.0001152692,0.0001057273,0.00005134625],"domain_scores_gemma":[0.9996576,0.0001790173,0.00004337163,0.00003091972,0.000066788,0.00002227141],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004135092,0.00009327239,0.006012144,0.000296361,0.0001932809,0.0003290353,0.0001969121,0.7104586,0.03362928,0.0272852,0.003587069,0.2175054],"study_design_scores_gemma":[0.000003863609,0.00001695102,0.0003761456,0.000003319869,0.00001076955,0.00004795006,0.000003215666,0.9960788,0.001154927,0.001921752,0.0003735033,0.000008775867],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03319757,0.0005491319,0.9638931,0.0003330068,0.00005915559,0.00003723766,0.0001584188,0.0005847931,0.001187546],"genre_scores_gemma":[0.7400188,0.001117885,0.251173,0.000226576,0.0001224916,0.0001855916,0.0006775374,0.0001238494,0.006354252],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006766479,"threshold_uncertainty_score":0.01345414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02762105584225804,"score_gpt":0.2736510672260924,"score_spread":0.2460300113838344,"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."}}