{"id":"W2885691317","doi":"10.1016/j.indcrop.2018.07.064","title":"A two-dimensional pyrolysis process to concentrate nicotine during tobacco leaf bio-oil production","year":2018,"lang":"en","type":"article","venue":"Industrial Crops and Products","topic":"Thermochemical Biomass Conversion Processes","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture and Agri-Food Canada; Western University","funders":"Office of Energy Research and Development; Agriculture and Agri-Food Canada; Natural Sciences and Engineering Research Council of Canada; Natural Resources Canada; Energy Council of Canada","keywords":"Nicotine; Pyrolysis; Condenser (optics); Chemistry; Chromatography; Extraction (chemistry); Boiling point; Distillation; Solvent; Nicotiana tabacum; Materials science; Pulp and paper industry; Organic chemistry; Biochemistry","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":[0.0001199966,0.0002932137,0.0002246169,0.0001699568,0.0002422252,0.0003840549,0.0002638715,0.0003147301,0.0006291308],"category_scores_gemma":[0.0001231895,0.0002345939,0.0003423054,0.0001586808,0.0001648646,0.0005045194,0.0003478107,0.0005575221,0.0003173578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002393142,"about_ca_system_score_gemma":0.0003555781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006176876,"about_ca_topic_score_gemma":0.001589459,"domain_scores_codex":[0.999908,0.000006112999,0.000006098249,0.00002262072,0.00004229614,0.00001487234],"domain_scores_gemma":[0.9999646,0.000007979763,0.000006503427,0.000006357515,0.00000756853,0.000007015685],"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":[0.00004936581,0.00003449768,0.0001127778,0.00004759594,0.000005156795,0.00005849947,0.00002394302,0.0002868952,0.9960716,0.0001647378,0.00003517604,0.003109772],"study_design_scores_gemma":[0.000009523354,0.00006346956,0.000602728,0.000002635999,0.00001012555,0.00007207803,0.0000128926,0.003029189,0.9951884,0.00004323492,0.0009580854,0.000007724562],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.963931,0.0009239723,0.03072332,0.0001190432,0.00009200507,0.00006609342,0.0001397725,0.0001398724,0.003864828],"genre_scores_gemma":[0.9830232,0.0005464349,0.01355634,0.00003406258,0.00001019307,0.00003175864,0.00009819004,0.00002386119,0.00267593],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006291308,"threshold_uncertainty_score":0.00210464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01844667138330863,"score_gpt":0.2294491631300141,"score_spread":0.2110024917467055,"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."}}