{"id":"W4246064280","doi":"10.2118/03-11-ge","title":"Economical Multilateral Well Technology For Canadian Heavy Oil","year":2003,"lang":"en","type":"article","venue":"Journal of Canadian Petroleum Technology","topic":"Drilling and Well Engineering","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Casing; Pace; Capital cost; Process (computing); Engineering; Operations management; Computer science; Petroleum engineering; Geology; Electrical engineering","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":[0.0004728321,0.0004123077,0.0002019505,0.001598442,0.001461399,0.001292195,0.00100202,0.0005669643,0.01101361],"category_scores_gemma":[0.0006537919,0.0002450772,0.0003773948,0.001164765,0.000552684,0.0009953154,0.0009923427,0.0006445776,0.001369736],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006507281,"about_ca_system_score_gemma":0.005607263,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2077637,"about_ca_topic_score_gemma":0.3549439,"domain_scores_codex":[0.9987022,0.00004440928,0.00002691587,0.0001001787,0.001007036,0.0001192527],"domain_scores_gemma":[0.9995649,0.0000196921,0.0000242467,0.00004184163,0.0003078236,0.00004158711],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003295522,0.0002572894,0.0049477,0.0005205158,0.00003267306,0.00089654,0.000674843,0.0688643,0.3203176,0.1552656,0.01990402,0.4279894],"study_design_scores_gemma":[0.0001694576,0.0007584005,0.0146213,0.0001366895,0.0001096567,0.0008723615,0.0007437119,0.1467956,0.3534813,0.01457716,0.46742,0.0003144981],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2534712,0.001333025,0.4704405,0.00155377,0.0005044724,0.001127869,0.001521342,0.005106261,0.2649415],"genre_scores_gemma":[0.795028,0.0006222866,0.1514061,0.0001193715,0.00001874537,0.0001387279,0.0005737722,0.0001909697,0.05190199],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7922363,"threshold_uncertainty_score":0.4131087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004792212733431111,"score_gpt":0.173093556057059,"score_spread":0.1683013433236279,"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."}}