{"id":"W4232516169","doi":"10.1016/j.fop.2021.07.007","title":"Canada: Cancarb – carbon black","year":2021,"lang":"en","type":"article","venue":"Focus on Pigments","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Carbon black; Materials science; Composite material","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005037974,0.0001158011,0.0001825174,0.00009209132,0.00008769955,0.00009714221,0.0002716525,0.00004833432,0.0002433426],"category_scores_gemma":[0.0004139525,0.00009490344,0.00006128148,0.0005765032,0.00002609097,0.00005163936,0.00005084436,0.0001035166,0.00009333368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001148603,"about_ca_system_score_gemma":0.0006831011,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2571435,"about_ca_topic_score_gemma":0.6009738,"domain_scores_codex":[0.9972042,0.0001134101,0.0003780175,0.000441815,0.001609107,0.0002534355],"domain_scores_gemma":[0.9987598,0.0002024281,0.0001150936,0.0005248971,0.0002678912,0.00012986],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002854922,0.0009385922,0.1133232,0.00003182848,0.0003738929,0.001346586,0.001943599,0.02461635,0.005067877,0.02422062,0.4526341,0.3752179],"study_design_scores_gemma":[0.005475929,0.0005734728,0.2039174,0.0002884252,0.0001688146,0.00004568286,0.007244742,0.1348079,0.03330732,0.2156237,0.3962663,0.002280381],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8927792,0.0001373176,0.0002519517,0.002832255,0.0008831778,0.00007491167,0.00004041702,0.00002592588,0.1029748],"genre_scores_gemma":[0.9917268,0.00002354808,0.00008572816,0.0008756435,0.00005357628,0.000005993463,0.000008498361,0.000009956698,0.007210311],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3729375,"threshold_uncertainty_score":0.7478032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07870479720353546,"score_gpt":0.3298741896364769,"score_spread":0.2511693924329414,"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."}}