{"id":"W4403827870","doi":"10.1002/cnl2.180","title":"Inside Back Cover Image: Carbon Neutralization, Volume 3, Issue 6, November 2024","year":2024,"lang":"en","type":"paratext","venue":"Carbon Neutralization","topic":"COVID-19 impact on air quality","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Cover (algebra); Neutralization; Volume (thermodynamics); Image (mathematics); Carbon fibers; Environmental science; Materials science; Computer science; Computer vision; Engineering; Composite material; Physics; Virology; Medicine; Mechanical engineering; Thermodynamics","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000545132,0.001193584,0.0009808776,0.0003602889,0.0001439866,0.0006650372,0.0007791126,0.001142652,0.08977193],"category_scores_gemma":[0.0001670761,0.001274127,0.0003535232,0.002175137,0.0004586008,0.0007190119,0.0005997546,0.001003457,0.08256786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002101953,"about_ca_system_score_gemma":0.0003086556,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006711902,"about_ca_topic_score_gemma":0.0005123165,"domain_scores_codex":[0.9939423,0.0004924076,0.001340032,0.001915334,0.001227134,0.001082747],"domain_scores_gemma":[0.9971917,0.0001220528,0.0005992242,0.001480354,0.000120069,0.0004866462],"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":[0.0000373898,0.0001268523,0.001740401,0.0007813381,0.00007833224,0.00002977653,0.00066119,0.02465654,0.005066729,0.00004719001,0.966567,0.0002072951],"study_design_scores_gemma":[0.0005796494,0.0001134387,0.002012485,0.0003600039,0.000298165,0.00001970724,0.00003651336,0.02543752,0.004462619,0.0002167793,0.9648927,0.001570382],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.03361883,0.0013505,0.001314373,0.005206062,0.01726648,0.002850926,0.0005506086,0.000522882,0.9373193],"genre_scores_gemma":[0.07033972,0.001144061,0.0001749713,0.005755681,0.002045477,0.000158587,0.002489383,0.0005637598,0.9173284],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.03672088,"threshold_uncertainty_score":0.9999025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01751641155336805,"score_gpt":0.2935102844968436,"score_spread":0.2759938729434755,"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."}}