{"id":"W7068912888","doi":"","title":"COLD RIGHTS","year":2022,"lang":"en","type":"other","venue":"Goldsmiths (University of London)","topic":"Probability and Statistical Research","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Politics; Commission; State (computer science); Economic Justice; Cold war; Arctic; Global warming; Action (physics)","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":[],"consensus_categories":[],"category_scores_codex":[0.003144749,0.0005550946,0.0004510607,0.0008858065,0.005339552,0.008546533,0.001128389,0.004201344,0.1644371],"category_scores_gemma":[0.007967902,0.0002678288,0.0004688136,0.001077274,0.005361775,0.005577251,0.005430046,0.004825873,0.04347239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002852579,"about_ca_system_score_gemma":0.003958065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006633806,"about_ca_topic_score_gemma":0.00908308,"domain_scores_codex":[0.995971,0.0009871798,0.0001859764,0.0007734609,0.001184516,0.0008978359],"domain_scores_gemma":[0.9973878,0.0006604459,0.0001837173,0.0007907862,0.0006355275,0.0003417343],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001437789,0.00001249408,0.000321426,0.00003372047,0.000002777228,0.00008473566,0.0008313211,0.00005168497,0.0001735156,0.8145562,0.1537557,0.030162],"study_design_scores_gemma":[0.000003015821,0.000006973017,0.0002583991,0.0000736974,0.000001338974,0.00009246133,0.0002393619,0.00003327427,0.00008704787,0.0305048,0.9686937,0.000005707919],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001137235,0.001014886,0.001077447,0.007602374,0.0007048649,0.00002472267,0.0002233231,0.00004998243,0.9881651],"genre_scores_gemma":[0.05686954,0.001657223,0.0006752479,0.01221967,0.0009108708,0.00009884543,0.0004521037,0.0001473078,0.9269691],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1644371,"threshold_uncertainty_score":0.550097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03361481503983179,"score_gpt":0.2728840241521003,"score_spread":0.2392692091122685,"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."}}