{"id":"W2062904142","doi":"10.1016/j.energy.2015.03.070","title":"Greenhouse gas abatement costs of hydrogen production from underground coal gasification","year":2015,"lang":"en","type":"article","venue":"Energy","topic":"Mining and Gasification Technologies","field":"Engineering","cited_by":52,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Underground coal gasification; Greenhouse gas; Tonne; Waste management; Environmental science; Life-cycle assessment; Carbon capture and storage (timeline); Engineering; Coal; Environmental engineering; Coal gasification; Production (economics); Climate change; Economics","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":[0.0005307187,0.0003754305,0.0003082381,0.0008746426,0.0004267337,0.0006840566,0.0004824398,0.0005578399,0.003939303],"category_scores_gemma":[0.0009806168,0.0002861554,0.0009174179,0.0006525285,0.0003633938,0.0008968859,0.0002927308,0.0005734865,0.0002611682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002784749,"about_ca_system_score_gemma":0.001571758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02154888,"about_ca_topic_score_gemma":0.02536105,"domain_scores_codex":[0.9997188,0.00006932315,0.000009116394,0.00002913045,0.00009299192,0.0000806459],"domain_scores_gemma":[0.999403,0.0003972532,0.0000404506,0.00002902963,0.0001023883,0.00002789554],"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":[0.006469273,0.0005653521,0.0403656,0.0005531085,0.0003640129,0.00137105,0.0001141352,0.8115831,0.04960644,0.02716864,0.002817505,0.05902171],"study_design_scores_gemma":[0.0003628437,0.001823325,0.1521768,0.0001180519,0.001031599,0.0005671256,0.001557594,0.663434,0.1516061,0.02038267,0.006776835,0.0001629802],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9860731,0.0002571235,0.002253176,0.0001850164,0.00003753828,0.0000316545,0.001206508,0.00003890817,0.009916913],"genre_scores_gemma":[0.998106,0.00008916545,0.0003006058,0.000006809168,0.000003186153,0.00000811734,0.0002490991,0.000005004049,0.001231921],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02154888,"threshold_uncertainty_score":0.04284686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.031481040737962,"score_gpt":0.2285156741792294,"score_spread":0.1970346334412674,"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."}}