{"id":"W2915140887","doi":"10.2118/0312-0090-jpt","title":"Technology Focus: Heavy Oil (March 2012)","year":2012,"lang":"en","type":"article","venue":"Journal of Petroleum Technology","topic":"Petroleum Processing and Analysis","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Oil reserves; Petroleum industry; Petroleum; Process (computing); Enhanced oil recovery; Petroleum engineering; Variety (cybernetics); Work (physics); Quality (philosophy); Computer science; Engineering management; Environmental science; Construction engineering; Biochemical engineering; Engineering; Mechanical engineering; Environmental engineering; Chemistry; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005822058,0.0003207266,0.0008026762,0.00210616,0.0001832133,0.00003611653,0.001063978,0.0008559496,0.000681784],"category_scores_gemma":[0.0003628482,0.0002751889,0.0003202814,0.001116407,0.0004088175,0.0004316049,0.0002145059,0.001624951,0.000115218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002221729,"about_ca_system_score_gemma":0.0001591736,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005966099,"about_ca_topic_score_gemma":0.000006418496,"domain_scores_codex":[0.9973875,0.00002563973,0.0009152585,0.0002582639,0.0004545816,0.0009587786],"domain_scores_gemma":[0.997889,0.00006723432,0.0009086536,0.0006023711,0.0003120202,0.0002206596],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001702106,0.0008990895,0.0530575,0.0001736725,0.0006960944,0.0001630477,0.00007362704,0.0000245366,0.3941113,0.003058411,0.004552008,0.5430205],"study_design_scores_gemma":[0.002245906,0.0003040681,0.0001549375,0.0003534399,0.0005035248,0.004246105,0.001773643,0.0001654081,0.21455,0.003981699,0.7710218,0.0006994591],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9061359,0.03499677,0.001684218,0.02161349,0.0004211018,0.000004299372,0.00001253876,0.0004842162,0.03464749],"genre_scores_gemma":[0.9817653,0.0006738311,0.003652649,0.00006419211,0.0007106836,0.000009567233,0.00000199225,0.00004976039,0.013072],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7664698,"threshold_uncertainty_score":0.99997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009171133611341132,"score_gpt":0.253155747187612,"score_spread":0.2439846135762709,"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."}}