{"id":"W1998280188","doi":"10.2118/2006-027","title":"Coalbed Characterization Studies With X-Ray Computerized Tomography (CT) and Micro CT Techniques","year":2006,"lang":"en","type":"article","venue":"Canadian International Petroleum Conference","topic":"Mineral Processing and Grinding","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Tomography; Characterization (materials science); X-ray; Computed tomography; Nuclear medicine; Medical physics; Computer science; Materials science; Radiology; Medicine; Optics; Physics; Nanotechnology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005006912,0.0001507819,0.0001487932,0.0002990768,0.00008139316,0.0001610903,0.000134181,0.00001537207,0.00002741196],"category_scores_gemma":[0.000006257257,0.0001427128,0.00001933005,0.0000928088,0.00007226403,0.0001739961,0.00001349802,0.0001023374,0.00000364788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000113387,"about_ca_system_score_gemma":0.00005458285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004201213,"about_ca_topic_score_gemma":0.01270405,"domain_scores_codex":[0.9993618,0.00000950673,0.0001565644,0.000175022,0.000106146,0.0001909794],"domain_scores_gemma":[0.999656,0.00001876797,0.00003924204,0.00007695524,0.0001143133,0.00009468468],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001391932,0.0001221743,0.2569156,0.001024876,0.001742545,0.00138657,0.001418014,0.01850982,0.6309429,0.02510716,0.01495233,0.04773879],"study_design_scores_gemma":[0.003393119,0.0002995266,0.3257979,0.002383321,0.0001494853,0.000942437,0.000637432,0.2517228,0.03553917,0.001857729,0.3740031,0.003273932],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922321,0.0001107683,0.002500227,0.0004212667,0.0002213547,0.00006185985,0.00007171839,0.000160569,0.004220173],"genre_scores_gemma":[0.9975032,0.00005542941,0.001471981,0.0001070628,0.0001282817,0.00002256726,0.0001566916,0.00001813872,0.0005366514],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5954037,"threshold_uncertainty_score":0.7089159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01074614605423936,"score_gpt":0.2121328647491778,"score_spread":0.2013867186949384,"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."}}