{"id":"W2362735951","doi":"","title":"Based on GA and ANN Random Plan Model for Reservor Parameter Predication","year":2005,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bottleneck; Computer science; Artificial neural network; Plan (archaeology); Genetic algorithm; Artificial intelligence; Mathematical optimization; Algorithm; Machine learning; Mathematics; Geology","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":[0.0004150726,0.0005750966,0.0005945857,0.000535767,0.0002315453,0.0005514835,0.0007317049,0.0005180861,0.001229455],"category_scores_gemma":[0.001108047,0.0002822875,0.0005216788,0.0005580446,0.0003452897,0.0008405477,0.00021984,0.0004583173,0.0001972036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007161014,"about_ca_system_score_gemma":0.0008065166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01453087,"about_ca_topic_score_gemma":0.01204764,"domain_scores_codex":[0.9997222,0.00009721682,0.00001076069,0.00006248718,0.00007991661,0.00002740521],"domain_scores_gemma":[0.9996678,0.0001951901,0.00003162607,0.00002098099,0.00007241737,0.00001199729],"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":[0.0000161262,0.000009333315,0.0003747432,0.00001336328,0.00001584746,0.00002367438,0.000009698857,0.9840631,0.0004127726,0.002438976,0.0002379391,0.01238442],"study_design_scores_gemma":[0.000002177098,0.000006167569,0.00006282851,0.000001159242,0.000003055382,0.00000552215,0.000001381274,0.998995,0.0001184955,0.0006833486,0.0001188418,0.00000209409],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02849894,0.0002353197,0.9666405,0.0001804748,0.00003871131,0.00004507702,0.00006828798,0.0005236017,0.003769033],"genre_scores_gemma":[0.7932726,0.0003694243,0.2006809,0.00009655961,0.00003369093,0.0002326515,0.0002279322,0.0000788871,0.005007518],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01453087,"threshold_uncertainty_score":0.02889258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02077880619971205,"score_gpt":0.2649585900913042,"score_spread":0.2441797838915921,"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."}}