{"id":"W4400546556","doi":"10.1007/s43508-024-00093-6","title":"Exploring coherence, learning and directionality in policy mixes for sustainability transition: the case of the Norwegian maritime transport’s decarbonization","year":2024,"lang":"en","type":"article","venue":"Global Public Policy and Governance","topic":"Sustainability and Climate Change Governance","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Rimouski","funders":"","keywords":"Norwegian; Sustainability; Coherence (philosophical gambling strategy); Directionality; Policy learning; Physics; Computer science; Ecology; Linguistics","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":[],"consensus_categories":[],"category_scores_codex":[0.000504846,0.0001310172,0.0001354752,0.00001626572,0.0002627934,0.00006262358,0.0001301989,0.00005642545,0.00002116989],"category_scores_gemma":[0.0006810906,0.0000941299,0.00006301863,0.0009887608,0.0004860154,0.0005432191,0.00007830366,0.0001356949,3.557331e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008187752,"about_ca_system_score_gemma":0.0001863939,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03995991,"about_ca_topic_score_gemma":0.01490678,"domain_scores_codex":[0.9988638,0.0001048619,0.0002244041,0.0003255601,0.0001679298,0.0003134407],"domain_scores_gemma":[0.9995262,0.0001479385,0.00007782594,0.0001518181,0.00003255166,0.00006368801],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001463331,0.0001884107,0.4753707,0.001201012,0.00003744667,0.00006691639,0.01175395,0.0007451288,0.00005238108,0.4071317,0.0001394452,0.1031666],"study_design_scores_gemma":[0.0002851436,0.00003820456,0.9414496,0.00005760678,0.00001350802,0.0001425714,0.002889374,0.0009794644,0.00002907641,0.03876125,0.01520831,0.0001458482],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9679863,0.0004051162,0.0001029648,0.02899626,0.00006280439,0.0004273667,0.000258461,0.00002497798,0.001735728],"genre_scores_gemma":[0.9991614,0.0002631389,0.00001621135,0.0002186524,0.00007883031,0.0001143055,0.000003308118,0.000006101137,0.0001381115],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4660789,"threshold_uncertainty_score":0.966433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02401301121850372,"score_gpt":0.2689912747907467,"score_spread":0.244978263572243,"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."}}