{"id":"W4401207576","doi":"10.1007/s40098-024-01032-2","title":"Meta-Heuristic-Based Machine Learning Techniques for Soil Stress Prediction in Embankment Dams During Construction","year":2024,"lang":"en","type":"article","venue":"Indian geotechnical journal","topic":"Dam Engineering and Safety","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Adaptive neuro fuzzy inference system; Artificial neural network; Firefly algorithm; Heuristic; Engineering; Machine learning; Computer science; Particle swarm optimization; Fuzzy logic; Artificial intelligence; Fuzzy control system","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005049303,0.0002138182,0.000291512,0.0004347159,0.0001122389,0.0001462616,0.0001382397,0.0001962083,0.00004880315],"category_scores_gemma":[0.00005844966,0.0001955406,0.0002135236,0.0002455841,0.00003535632,0.0001604785,0.00001820363,0.00118744,0.000006491262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002755551,"about_ca_system_score_gemma":0.00003907616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008825659,"about_ca_topic_score_gemma":0.000006280715,"domain_scores_codex":[0.998715,0.00003495125,0.0004863286,0.0001970352,0.000215611,0.0003510345],"domain_scores_gemma":[0.9995871,0.00009586362,0.00003592937,0.0001244211,0.00003044949,0.0001263026],"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":[0.00002127883,0.00002759679,0.0002001523,0.0004174223,0.0003225638,0.0001389984,0.00007441427,0.9800987,0.003546962,0.000102272,0.0001677422,0.0148819],"study_design_scores_gemma":[0.0007018897,0.0001983781,0.001140552,0.0007544325,0.000400784,0.0008305945,0.00004379242,0.9468154,0.03354718,0.0006982483,0.01440379,0.0004649451],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1793102,0.004269792,0.808032,0.0005277254,0.002025857,0.0007382966,0.0003588672,0.004285582,0.0004516758],"genre_scores_gemma":[0.9935229,0.0001914928,0.005722216,0.000008920169,0.000316706,0.00009185603,0.00003296269,0.00006279449,0.00005009895],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8142127,"threshold_uncertainty_score":0.7973916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01116440951077747,"score_gpt":0.22594831764085,"score_spread":0.2147839081300726,"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."}}