{"id":"W2038006265","doi":"10.1175/jtech1987.1","title":"SPARC: New Cloud, Snow, and Cloud Shadow Detection Scheme for Historical 1-km AVHHR Data over Canada","year":2007,"lang":"en","type":"article","venue":"Journal of Atmospheric and Oceanic Technology","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":118,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Pixel; Advanced very-high-resolution radiometer; Remote sensing; Snow; Sky; Cloud computing; Satellite; Shadow (psychology); Image resolution; Meteorology; Environmental science; Radiometry; Polar orbit; Weather satellite; Computer science; Geology; Geography; Artificial intelligence; Astronomy; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004347395,0.0002048409,0.0003660529,0.000001858818,0.0001830813,0.00001879396,0.0004725874,0.0002476942,0.0001976886],"category_scores_gemma":[0.0001803537,0.0001735949,0.00004543325,0.0003485288,0.0001806545,0.0001902033,0.0003759094,0.0003743417,0.000001914421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007020249,"about_ca_system_score_gemma":0.0001630545,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0253438,"about_ca_topic_score_gemma":0.04764012,"domain_scores_codex":[0.9984087,0.0000125521,0.0005208324,0.0003528229,0.0002860523,0.000419092],"domain_scores_gemma":[0.9988658,0.00009989625,0.0004049302,0.0003509441,0.00002408603,0.0002543436],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006007783,0.0001664671,0.186432,0.00003797636,0.0001707693,0.0001839394,0.0001496354,0.00004872095,0.006902904,0.0008723334,0.2392129,0.5652216],"study_design_scores_gemma":[0.002449927,0.001210958,0.08273382,0.00004038641,0.000151227,0.001136711,0.0007388135,0.003832577,0.0008773051,0.002813469,0.903458,0.0005568125],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9150255,0.002452467,0.07956459,0.001379038,0.001173378,0.0001637729,0.000004609494,0.00003345229,0.0002031739],"genre_scores_gemma":[0.9503542,0.0003746236,0.04736154,0.0003720233,0.000606213,9.309173e-7,0.000001356378,0.00002794518,0.0009011866],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6642451,"threshold_uncertainty_score":0.9811465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009953319322166896,"score_gpt":0.2207516784945713,"score_spread":0.2107983591724044,"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."}}