{"id":"W1482266527","doi":"10.1002/2014jd021858","title":"The influence of canopy snow parameterizations on snow albedo feedback in boreal forest regions","year":2014,"lang":"en","type":"article","venue":"Journal of Geophysical Research Atmospheres","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; University of Waterloo","funders":"","keywords":"Albedo (alchemy); Snow; Environmental science; Boreal; Taiga; Canopy; Atmospheric sciences; Climatology; Climate change; Evergreen; Meteorology; Geography; Ecology; Geology","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":[0.0009020408,0.0001150511,0.0002693027,0.00001901088,0.0004054803,0.00008259057,0.0005353563,0.00005010383,0.00005987003],"category_scores_gemma":[0.003979169,0.0000692421,0.0001164237,0.0008840749,0.0005077417,0.0001880153,0.00003867091,0.0005226512,0.00003094914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001884396,"about_ca_system_score_gemma":0.0001926397,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01077724,"about_ca_topic_score_gemma":0.02930465,"domain_scores_codex":[0.9977359,0.0003104207,0.0004803996,0.0001504717,0.0008686142,0.0004541928],"domain_scores_gemma":[0.9929885,0.005843295,0.000220759,0.0002712865,0.0004993569,0.0001768342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000447098,0.0002099496,0.8532727,0.00001960585,0.00007727028,0.00001683878,0.0003827765,0.07221344,0.00006766237,0.0102695,0.006663749,0.05635942],"study_design_scores_gemma":[0.0002990426,0.0009355889,0.9728812,0.0001191886,0.000006494085,0.000002563808,0.000405604,0.00521067,0.00002510828,0.01045952,0.009583822,0.00007119063],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99503,0.0001598417,0.00009955168,0.002374697,0.00009452055,0.0001423359,0.00001049635,0.000003795876,0.002084699],"genre_scores_gemma":[0.9983164,0.0005697821,0.0005476496,0.00008585267,0.0001970374,0.000002531017,0.000004648989,0.000004855255,0.0002712258],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1196085,"threshold_uncertainty_score":0.9958101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03346980787217455,"score_gpt":0.2920897082377295,"score_spread":0.2586199003655549,"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."}}