{"id":"W3125950361","doi":"10.2139/ssrn.3122261","title":"The Carbon Abatement Game","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Natural resource economics; Economics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009703624,0.0007580384,0.001179268,0.0004369552,0.0007706896,0.002818175,0.001224495,0.003508676,0.01313008],"category_scores_gemma":[0.00426004,0.0003738181,0.0005733365,0.0004019383,0.001958426,0.00301813,0.001379443,0.002249843,0.0006855962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001973744,"about_ca_system_score_gemma":0.001812305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005570202,"about_ca_topic_score_gemma":0.003410901,"domain_scores_codex":[0.9992156,0.0003502719,0.0000261409,0.0001228933,0.0001217871,0.0001633543],"domain_scores_gemma":[0.9983528,0.001154541,0.0001041182,0.0000745635,0.0000800277,0.0002340036],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001959322,0.00009330553,0.0005122573,0.00006965353,0.00004628157,0.0002758613,0.00009603602,0.0871634,0.0008524617,0.8997915,0.005191626,0.005711625],"study_design_scores_gemma":[0.00014614,0.00006188018,0.0003834908,0.00001710927,0.00001821923,0.0000877089,0.00006819763,0.2134813,0.0001953983,0.7819928,0.003523509,0.00002424293],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.40315,0.001292369,0.2070273,0.01965198,0.0003584043,0.0002784096,0.001504025,0.0002265071,0.3665109],"genre_scores_gemma":[0.9639564,0.000369233,0.00391463,0.0003949628,0.00009227427,0.00009409116,0.0001371944,0.00002038166,0.03102083],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01313008,"threshold_uncertainty_score":0.04392445,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03826320571331038,"score_gpt":0.2442579666738345,"score_spread":0.2059947609605241,"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."}}