{"id":"W4402640925","doi":"10.1016/j.indcrop.2024.119665","title":"Optimizing combinatorial pretreatment for efficient separation and utilization of reed components","year":2024,"lang":"en","type":"article","venue":"Industrial Crops and Products","topic":"Catalysis for Biomass Conversion","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Liaoning Revitalization Talents Program; Natural Science Foundation of Liaoning Province; National Natural Science Foundation of China","keywords":"Separation (statistics); Chemistry; Mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001439052,0.00008470682,0.0001196221,0.00007689059,0.00004216399,0.00004852678,0.00002302858,0.00007867189,0.000002321358],"category_scores_gemma":[0.00003651912,0.00007839513,0.00001914159,0.0001596758,0.00002561672,0.00006180879,0.00001819754,0.00004567358,6.46096e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003944392,"about_ca_system_score_gemma":0.00001538429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002164121,"about_ca_topic_score_gemma":9.273875e-7,"domain_scores_codex":[0.9994975,0.0000112612,0.0001526563,0.0001677363,0.00008767164,0.00008312944],"domain_scores_gemma":[0.9997946,0.00003323915,0.00002172601,0.00008138319,0.00004080593,0.0000282626],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00108554,0.0002354571,0.0007052951,0.002073215,0.0007382066,0.00001018126,0.005724635,0.02383679,0.8267069,0.006500367,0.009184597,0.1231988],"study_design_scores_gemma":[0.003136588,0.0003719991,0.0003243954,0.0002562797,0.0002525747,0.00000732478,0.00007479009,0.3264259,0.6431849,0.0002195807,0.0254636,0.0002819943],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952806,0.001612215,0.0005383177,0.00009268156,0.001798173,0.0005201348,0.00004154138,0.00007042965,0.00004594295],"genre_scores_gemma":[0.9993746,0.0000391376,0.0002009173,8.822474e-7,0.0002205937,0.00001008827,0.0001181886,0.00001228442,0.00002327141],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3025892,"threshold_uncertainty_score":0.3196861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05341499644976554,"score_gpt":0.2683756886376802,"score_spread":0.2149606921879146,"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."}}