{"id":"W4402307188","doi":"10.18280/ts.410447","title":"Optimizing Lung Cancer Classification with Extreme Learning Machine and Ant Lion Optimization for Enhanced Early Detection","year":2024,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Machine Learning and ELM","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"ANT; Artificial intelligence; Extreme learning machine; Computer science; Machine learning; Lung cancer; Pattern recognition (psychology); Medicine; Pathology; Artificial neural network","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":[0.001451183,0.0007995805,0.001320557,0.0006085792,0.0003385302,0.0008931048,0.001078123,0.001477026,0.001368949],"category_scores_gemma":[0.003693285,0.0004924294,0.0007913026,0.0005176759,0.0008157993,0.0008130481,0.0009862666,0.001085841,0.0003316303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005607535,"about_ca_system_score_gemma":0.0008044193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002805169,"about_ca_topic_score_gemma":0.002262295,"domain_scores_codex":[0.999494,0.000217212,0.00002525116,0.00008564954,0.0001134878,0.0000644987],"domain_scores_gemma":[0.9985555,0.001010225,0.0001174297,0.00006689371,0.000198174,0.00005184796],"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":[0.0001521127,0.00005284611,0.0006459584,0.0000419085,0.000044049,0.00004771508,0.00003071863,0.955373,0.002126823,0.002708178,0.000903381,0.03787334],"study_design_scores_gemma":[0.000002550471,0.000008270361,0.00003602612,9.770461e-7,0.000001559306,0.000003985905,0.000001210013,0.9991857,0.0001421758,0.0005860276,0.00003024001,0.000001135614],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02680161,0.000200096,0.9716329,0.000217719,0.00003787731,0.00001772038,0.0000216604,0.0002886063,0.0007818032],"genre_scores_gemma":[0.768182,0.0001607785,0.2262088,0.0002619697,0.00009989013,0.000123331,0.0001344765,0.0001538216,0.004675006],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002805169,"threshold_uncertainty_score":0.007674634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01658058119530142,"score_gpt":0.2532403063502602,"score_spread":0.2366597251549588,"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."}}