{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008329096,0.001110895,0.0006109614,0.001486334,0.004972299,0.00381656,0.001505105,0.00258268,0.3954061],"category_scores_gemma":[0.002107926,0.000521347,0.0004707239,0.003209905,0.001455256,0.001331545,0.001580119,0.002049802,0.05901659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03455088,"about_ca_system_score_gemma":0.08258961,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9771702,"about_ca_topic_score_gemma":0.9857913,"domain_scores_codex":[0.9988097,0.00005133425,0.0000254939,0.0001365518,0.0006900335,0.0002869487],"domain_scores_gemma":[0.9967819,0.0001644147,0.0001002897,0.0001383121,0.002143199,0.0006718368],"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":[0.0001212388,0.00003849525,0.001188356,0.0001480947,0.00001281724,0.00009228324,0.00004731304,0.0006326372,0.0004558862,0.01285868,0.9206078,0.06379633],"study_design_scores_gemma":[0.00002044073,0.00001066195,0.002682308,0.00006834545,0.000005447652,0.00003504092,0.0001150891,0.0004924586,0.0003439989,0.001130862,0.99508,0.00001536451],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.007246678,0.007175819,0.001772023,0.03568713,0.003254552,0.0001717262,0.03701811,0.002367509,0.9053064],"genre_scores_gemma":[0.01641412,0.002040104,0.001146208,0.00152462,0.0001199618,0.00002772851,0.004002838,0.0005404112,0.974184],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3954061,"threshold_uncertainty_score":0.8623798,"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."}}