{"id":"W4234753699","doi":"10.2523/59767-ms","title":"Development of an Intelligent Systems Approach for Restimulation Candidate Selection","year":2000,"lang":"en","type":"article","venue":"","topic":"Hydraulic Fracturing and Reservoir Analysis","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Citation; Computer science; Selection (genetic algorithm); Download; Artificial intelligence; Library science; World Wide Web; Information retrieval","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002944244,0.0009492461,0.0008635239,0.001834836,0.00108401,0.002155595,0.002091214,0.001036016,0.006187759],"category_scores_gemma":[0.007654544,0.0004952743,0.001470941,0.0009776433,0.0009932498,0.001896712,0.002186482,0.001596884,0.002363604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001647855,"about_ca_system_score_gemma":0.002033299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004861321,"about_ca_topic_score_gemma":0.006653831,"domain_scores_codex":[0.9975945,0.0008145355,0.0002300421,0.000443881,0.0007795657,0.0001374648],"domain_scores_gemma":[0.9972154,0.001152966,0.0001604718,0.0002386075,0.001131752,0.0001008092],"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":[0.0002712414,0.000287645,0.002764858,0.0003751481,0.000215674,0.0004283432,0.0007615325,0.2251319,0.01356642,0.1386099,0.01014714,0.6074401],"study_design_scores_gemma":[0.00004933191,0.0001582169,0.0004827126,0.00006459867,0.00007603835,0.0001218222,0.0001666491,0.9420016,0.007789885,0.03135388,0.01769522,0.00004010403],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001915381,0.00007543097,0.9935169,0.000214356,0.00003021145,0.0001777311,0.00003565371,0.0006328609,0.003401455],"genre_scores_gemma":[0.08178616,0.0002021005,0.9102497,0.0002302329,0.0000674869,0.0005462489,0.0002392591,0.0001709973,0.006507847],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006187759,"threshold_uncertainty_score":0.02070016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01492921358727955,"score_gpt":0.238235488269459,"score_spread":0.2233062746821795,"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."}}