{"id":"W3202916798","doi":"10.30683/1927-7229.2020.09.02","title":"Brain Tumour Classification by Machine Learning Applications with Selected Biological Features: Towards A Newer Diagnostic Regime","year":2020,"lang":"en","type":"article","venue":"Journal of Analytical Oncology","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Calcutta; Council of Scientific and Industrial Research, India","keywords":"Support vector machine; Artificial intelligence; Pattern recognition (psychology); Computer science; Propidium iodide; Machine learning; Dimensionality reduction; Feature vector; Biology","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":[0.001645992,0.0005907614,0.00077665,0.001868282,0.0001988977,0.001765055,0.0006948112,0.0007335271,0.0006250115],"category_scores_gemma":[0.002523207,0.000192074,0.000494468,0.001001326,0.0004815134,0.001169303,0.0006103485,0.001017732,0.0005319833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003582228,"about_ca_system_score_gemma":0.0004631503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005074186,"about_ca_topic_score_gemma":0.0004392883,"domain_scores_codex":[0.9992531,0.0002018454,0.00007265595,0.000170012,0.000252135,0.00005018324],"domain_scores_gemma":[0.9987847,0.0004821695,0.0001930401,0.0001510764,0.000322863,0.00006610055],"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":[0.0003523185,0.000446745,0.02744591,0.0004341461,0.0001401759,0.0002997906,0.0003555341,0.02726129,0.09865991,0.005856296,0.002218791,0.8365291],"study_design_scores_gemma":[0.00004082127,0.0008573071,0.02839599,0.0001984968,0.0001832612,0.001094865,0.0003687589,0.8866024,0.05484848,0.01386495,0.0134256,0.0001190595],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2209157,0.005990698,0.7653869,0.001974923,0.0001795198,0.0001447057,0.0002924925,0.002268786,0.002846146],"genre_scores_gemma":[0.6507149,0.001782381,0.344501,0.0002667844,0.0003180397,0.0001366388,0.0005231202,0.00007965018,0.001677411],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001868282,"threshold_uncertainty_score":0.00870496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05006660998031629,"score_gpt":0.3082955174103325,"score_spread":0.2582289074300161,"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."}}