{"id":"W4389902778","doi":"10.1016/j.ngib.2023.11.006","title":"Modelling underground coal gasification: What to start with","year":2023,"lang":"en","type":"article","venue":"Natural Gas Industry B","topic":"Mining and Gasification Technologies","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Technology Futures; Western Canada Research Grid; Energi Simulation; Compute Canada","keywords":"Underground coal gasification; Coal; Clean coal; Situated; Engineering; Coal mining; Petroleum engineering; Construction engineering; Mining engineering; Computer science; Waste management; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0008487343,0.0008113083,0.001161456,0.0005758846,0.0006529743,0.002677478,0.002263914,0.003007175,0.006241448],"category_scores_gemma":[0.003427685,0.0006031587,0.001276772,0.0009982854,0.001513026,0.005438989,0.002772574,0.002618839,0.001529363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006701349,"about_ca_system_score_gemma":0.001626337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008480166,"about_ca_topic_score_gemma":0.006231301,"domain_scores_codex":[0.9996324,0.0001211378,0.00002699958,0.00005146971,0.0001212861,0.00004668812],"domain_scores_gemma":[0.9994143,0.00028485,0.00005265518,0.00007735006,0.000112404,0.00005849217],"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":[0.00007221076,0.00007427014,0.002877956,0.001092329,0.00006155274,0.000317864,0.0005194041,0.7475351,0.002764759,0.1827054,0.007394962,0.05458422],"study_design_scores_gemma":[0.00003319959,0.00006409204,0.0008548209,0.0005446709,0.00004071215,0.0001767968,0.000534308,0.7452975,0.002046657,0.1716219,0.07871341,0.00007183241],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04544738,0.01313235,0.8723965,0.01889642,0.001359954,0.0003018362,0.002126479,0.001712552,0.04462654],"genre_scores_gemma":[0.48353,0.03437991,0.4487022,0.002556653,0.0009802449,0.0009875959,0.002905198,0.002110806,0.02384742],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008480166,"threshold_uncertainty_score":0.02087969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04379498091386749,"score_gpt":0.2496047055847952,"score_spread":0.2058097246709277,"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."}}