{"id":"W2268360322","doi":"10.1021/bk-2011-1067.ch015","title":"Modify Existing Pulp and Paper Mills for Biorefinery Operations","year":2011,"lang":"en","type":"book-chapter","venue":"ACS symposium series","topic":"Advanced Cellulose Research Studies","field":"Materials Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"FPInnovations","funders":"","keywords":"Biorefinery; Pulp (tooth); Pulp and paper industry; Engineering; Manufacturing engineering; Operations management; Waste management; Business; Biofuel; Medicine; Dentistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"not_applicable","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"design_other","genre":"other","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002501135,0.0004998837,0.0002376654,0.0004371298,0.000357754,0.0010237,0.0009796385,0.000570051,0.02276583],"category_scores_gemma":[0.0003649931,0.0002239064,0.0003192629,0.0005540097,0.0001900366,0.001308433,0.0003907785,0.0007166995,0.01859156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000424066,"about_ca_system_score_gemma":0.0004758702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005300842,"about_ca_topic_score_gemma":0.001987257,"domain_scores_codex":[0.9998251,0.000009527743,0.000008226103,0.00003671449,0.00009568551,0.0000247657],"domain_scores_gemma":[0.9998652,0.0000235517,0.00001936745,0.00003469845,0.00004317007,0.00001408798],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001359518,0.0005506049,0.001460465,0.001354928,0.00001776492,0.0007804321,0.0004778568,0.003899858,0.2545443,0.02278296,0.03470195,0.679293],"study_design_scores_gemma":[0.00003787938,0.0002885772,0.003341104,0.0001982252,0.00002287339,0.0008711536,0.0002958969,0.002387111,0.110188,0.005843185,0.8764942,0.00003177419],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1550548,0.01572263,0.1425851,0.002003815,0.003583996,0.001141427,0.001366788,0.005501829,0.6730397],"genre_scores_gemma":[0.2596175,0.01430702,0.1931061,0.001537042,0.0004409979,0.0004133405,0.001194413,0.0008922997,0.5284912],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02276583,"threshold_uncertainty_score":0.07615936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05142152824037873,"score_gpt":0.2838916870017155,"score_spread":0.2324701587613367,"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."}}