{"id":"W4407957284","doi":"10.1016/j.apenergy.2025.125589","title":"Energy efficiency analysis of microwave treatment in rocks: from mine-to-mill operations","year":2025,"lang":"en","type":"article","venue":"Applied Energy","topic":"Mineral Processing and Grinding","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Mill; Engineering; Waste management; Microwave; Environmental science; Mining engineering; Forensic engineering; Mechanical engineering; Telecommunications","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":[0.0005232734,0.0002333925,0.0003987675,0.0006119786,0.0002088674,0.0004123955,0.0003840308,0.0003020873,0.001265095],"category_scores_gemma":[0.0006217729,0.0001682199,0.0004246072,0.0006624085,0.0002844344,0.0004592269,0.0002851191,0.0004568935,0.0003230818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003116843,"about_ca_system_score_gemma":0.000174058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009750224,"about_ca_topic_score_gemma":0.001211305,"domain_scores_codex":[0.9997003,0.00002546464,0.00001911122,0.00005778464,0.0001609676,0.00003638174],"domain_scores_gemma":[0.9997078,0.0001104686,0.00005146834,0.00004445374,0.00007703343,0.000008838864],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000681299,0.0002053345,0.01775275,0.0006573637,0.00006526746,0.0002813976,0.0002245666,0.02006692,0.8985831,0.001025845,0.0003735267,0.06008272],"study_design_scores_gemma":[0.0000132426,0.001032984,0.0432335,0.00003419404,0.00008303443,0.0001958213,0.0003098508,0.0318483,0.9198292,0.0003511866,0.003037699,0.00003097696],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9850062,0.001034143,0.01109434,0.00003698073,0.00001441697,0.00004023794,0.0002801379,0.00008931469,0.002404268],"genre_scores_gemma":[0.994423,0.0007891738,0.00368622,0.00001741867,0.000004807419,0.00002852484,0.0002225574,0.00002462106,0.0008037341],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001265095,"threshold_uncertainty_score":0.004232228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006455436287282781,"score_gpt":0.2139108248241197,"score_spread":0.2074553885368369,"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."}}