{"id":"W3206704895","doi":"","title":"Assessing prior emergent constraints on surface albedo feedback in CMIP6","year":2020,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Astro and Planetary Science","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Albedo (alchemy); Environmental science; Computer science; Remote sensing; Climatology; Meteorology; Geology; Geography; History","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":[0.001886725,0.0005325543,0.0004242868,0.0004808983,0.0006282377,0.001115556,0.0009245402,0.001326935,0.004363138],"category_scores_gemma":[0.01212359,0.0004912292,0.0004343288,0.0004997179,0.000505021,0.001849273,0.001101997,0.001295705,0.0008671577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000747146,"about_ca_system_score_gemma":0.000670717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01417283,"about_ca_topic_score_gemma":0.01478869,"domain_scores_codex":[0.9996057,0.00008159243,0.00001817576,0.0001417873,0.00006787946,0.00008483048],"domain_scores_gemma":[0.9940659,0.003616944,0.0004274043,0.000676667,0.0007177652,0.0004952703],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001792184,0.0002524712,0.6310281,0.0003978879,0.0003251847,0.0004706034,0.0004932384,0.2892313,0.02094743,0.004549114,0.007301447,0.04321115],"study_design_scores_gemma":[0.0001851228,0.0001270481,0.5199541,0.00008269238,0.00009126452,0.0001214141,0.0002678268,0.4660489,0.006557174,0.003764075,0.002731924,0.00006858721],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898916,0.0001740901,0.002383151,0.0005107204,0.00002993485,0.00001080262,0.002630125,0.0002678114,0.004101709],"genre_scores_gemma":[0.9973462,0.00003854672,0.000734596,0.00004555365,0.00002202165,0.000006470526,0.001623536,0.00006336253,0.0001196687],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01417283,"threshold_uncertainty_score":0.02818066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02854249686358894,"score_gpt":0.2608410474002502,"score_spread":0.2322985505366613,"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."}}