{"id":"W2968143057","doi":"10.1190/segam2019-3208817.1","title":"Improved well log classification using semi-supervised algorithms","year":2019,"lang":"en","type":"article","venue":"","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Machine learning; Artificial intelligence; Computer science; Algorithm; Semi-supervised learning; Supervised learning; Statistical classification; Labeled data; Artificial neural network","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003403541,0.001092141,0.001524216,0.001879661,0.0007309769,0.001802062,0.001980966,0.001321426,0.002412594],"category_scores_gemma":[0.007794685,0.000484761,0.001122783,0.001054905,0.0007846226,0.002822148,0.001226958,0.001741423,0.001329754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008711723,"about_ca_system_score_gemma":0.001664103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005059379,"about_ca_topic_score_gemma":0.006866411,"domain_scores_codex":[0.9984643,0.0005246079,0.0001107116,0.0003731251,0.0004016553,0.0001255105],"domain_scores_gemma":[0.9931938,0.002703141,0.0005600039,0.0009701572,0.002393339,0.0001796388],"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":[0.0003425306,0.0005040315,0.006643265,0.0001200906,0.00013402,0.000090849,0.0002076703,0.5265455,0.005070838,0.005434168,0.009011813,0.4458953],"study_design_scores_gemma":[0.000005528818,0.0000126945,0.0002838573,0.000003858519,0.000003883937,0.000008528857,0.0000139875,0.9968741,0.0008347495,0.001638593,0.0003139827,0.000006201888],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06528243,0.0002893375,0.9263769,0.0003548213,0.00009906898,0.0001630152,0.0002657286,0.004201684,0.002966961],"genre_scores_gemma":[0.5295432,0.0001550167,0.4625179,0.000231543,0.0001428252,0.0002271141,0.001682353,0.0004072249,0.005092751],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005059379,"threshold_uncertainty_score":0.01799989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03213491478872394,"score_gpt":0.2770539888188546,"score_spread":0.2449190740301307,"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."}}