{"id":"W4407941867","doi":"10.1016/j.biombioe.2025.107677","title":"Techno-economic evaluation of pulp and paper mill derived biochar, liquid and gaseous biofuel precursors: A British Columbia case study","year":2025,"lang":"en","type":"article","venue":"Biomass and Bioenergy","topic":"Thermochemical Biomass Conversion Processes","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Natural Resources Canada","funders":"Canadian Forest Service; Office of Energy Research and Development; Natural Resources Canada","keywords":"Biochar; Pulp and paper industry; Pulp (tooth); Pulp mill; Biofuel; Mill; Paper mill; Environmental science; Waste management; Chemistry; Engineering; Pyrolysis; Environmental engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"empirical","about_ca_system":false,"about_ca_topic":true,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"empirical","about_ca_system":false,"about_ca_topic":true,"confidence":"medium","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005808206,0.0005880741,0.000342881,0.001460411,0.002172706,0.002271974,0.001114431,0.0009084602,0.002173183],"category_scores_gemma":[0.001177395,0.0003195434,0.0002848016,0.002226439,0.0009296444,0.0004713426,0.0006572815,0.0007807941,0.0002340113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0293161,"about_ca_system_score_gemma":0.01130716,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9446697,"about_ca_topic_score_gemma":0.9741492,"domain_scores_codex":[0.9994654,0.00009440897,0.00001664067,0.00004813457,0.0002168955,0.0001584866],"domain_scores_gemma":[0.9992011,0.0002288778,0.00004927091,0.00003403276,0.0003838236,0.0001028678],"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":[0.007015967,0.00559086,0.2686456,0.001277873,0.0006108989,0.02189121,0.00237338,0.4154902,0.07637849,0.0157791,0.01435031,0.1705962],"study_design_scores_gemma":[0.001121509,0.002837268,0.4638397,0.0003701801,0.0007710207,0.001573707,0.02724944,0.3856334,0.06873753,0.003294008,0.04412243,0.0004498765],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9877853,0.0002340038,0.000181427,0.0001517541,0.000003187597,0.00006431982,0.0004074663,0.00001186831,0.01116059],"genre_scores_gemma":[0.9912661,0.0003880546,0.0005083329,0.00003005548,0.000001417819,0.0000273669,0.0002824479,0.000008186277,0.007488054],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05533034,"threshold_uncertainty_score":0.2127042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008519419454869281,"score_gpt":0.2198575179589389,"score_spread":0.2113380985040696,"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."}}