{"id":"W3124053448","doi":"10.18280/ria.340610","title":"Microarray Breast Cancer Data Clustering Using Map Reduce Based K-Means Algorithm","year":2020,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Breast cancer; Cluster analysis; Microarray analysis techniques; Cancer; Computer science; Microarray; Data mining; Algorithm; Bioinformatics; Artificial intelligence; Medicine; Internal medicine; Biology; Gene","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":[0.0004066743,0.0007253841,0.001106338,0.001565295,0.001195011,0.0008171219,0.001155631,0.0006285752,0.001538535],"category_scores_gemma":[0.001497202,0.0003501103,0.001190868,0.00206798,0.0002851852,0.0005309501,0.0006592602,0.0007012218,0.0009306499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00108478,"about_ca_system_score_gemma":0.002344288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02987993,"about_ca_topic_score_gemma":0.02006294,"domain_scores_codex":[0.9992977,0.00008727964,0.00004967493,0.0002183183,0.0002730358,0.00007396237],"domain_scores_gemma":[0.999574,0.00007765365,0.00003144842,0.0000531478,0.0002465946,0.0000171579],"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":[0.0004481226,0.0002989929,0.003346921,0.0003223682,0.0001868582,0.0001586772,0.0003463566,0.3690754,0.02485228,0.005274275,0.01818092,0.5775089],"study_design_scores_gemma":[0.00001860918,0.00004044793,0.001563274,0.000004924645,0.00001789947,0.00005710496,0.00006733031,0.9824582,0.008562354,0.00301186,0.004175191,0.00002283977],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04152651,0.0003600813,0.9486405,0.0003039783,0.00006982998,0.0003506396,0.001102081,0.006024565,0.001621856],"genre_scores_gemma":[0.1297596,0.0002256032,0.8639843,0.00006747634,0.00003223508,0.0006641999,0.00257855,0.0001517212,0.002536174],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02987993,"threshold_uncertainty_score":0.059412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08689772592350135,"score_gpt":0.3235900438027133,"score_spread":0.2366923178792119,"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."}}