{"id":"W4389359545","doi":"10.2139/ssrn.4655477","title":"Machine Learning Techniques in Eor Screening Using Semi-Supervised Label Propagation","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Hydrocarbon exploration and reservoir analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Machine learning; Artificial intelligence","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":[0.003998882,0.001544635,0.001708332,0.002885261,0.001217538,0.002086539,0.003336547,0.002460359,0.00361394],"category_scores_gemma":[0.009871993,0.0007095822,0.001370765,0.002025297,0.001052614,0.002604711,0.002065215,0.002806591,0.002578444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005988777,"about_ca_system_score_gemma":0.001593845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003628981,"about_ca_topic_score_gemma":0.006101728,"domain_scores_codex":[0.9976052,0.0009725509,0.0001350298,0.0004727033,0.0006274179,0.0001871009],"domain_scores_gemma":[0.9898635,0.006217452,0.0007330705,0.001074221,0.001908411,0.000203446],"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":[0.0005495572,0.0007115354,0.003889006,0.0005442394,0.0002172984,0.0002388574,0.0002340001,0.285954,0.03001236,0.008530997,0.008275357,0.6608428],"study_design_scores_gemma":[0.00001463085,0.00004463112,0.0003341642,0.00001587849,0.00001827571,0.00004640216,0.0000184333,0.9880493,0.006748341,0.003978646,0.0007170457,0.00001411836],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01803865,0.0002762454,0.9755889,0.0002149974,0.00005620085,0.0001447424,0.0002992658,0.00374358,0.001637398],"genre_scores_gemma":[0.2815945,0.0002868523,0.7091986,0.000359816,0.0001342484,0.0003163957,0.001466449,0.0007751097,0.00586801],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003998882,"threshold_uncertainty_score":0.02114832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02666398745501996,"score_gpt":0.2652746901960144,"score_spread":0.2386107027409944,"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."}}