{"id":"W4297977080","doi":"","title":"Characterization, validation and intercomparison of clumping index maps from POLDER, MODIS, and MISR data","year":2014,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Index (typography); Environmental science; Remote sensing; Computer science; 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":[0.002000257,0.0002009113,0.000330854,0.0001172321,0.0001657904,0.0003233137,0.0005813041,0.000192266,0.00007563114],"category_scores_gemma":[0.0004236448,0.0001921658,0.00003513692,0.0001045772,0.0001565495,0.0001845753,0.0004403313,0.0002995429,0.000005596549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004853657,"about_ca_system_score_gemma":0.00006381083,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01692015,"about_ca_topic_score_gemma":0.006157859,"domain_scores_codex":[0.9967366,0.001849827,0.0004104588,0.0006108478,0.0002268748,0.0001653346],"domain_scores_gemma":[0.9970971,0.0006523571,0.000446946,0.001324966,0.0003562182,0.0001224594],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004598986,0.0001293124,0.4323716,0.0003574937,0.0001364454,0.000001680405,0.01085859,0.0003096293,0.002423335,0.0004317129,0.0004333663,0.5525008],"study_design_scores_gemma":[0.0004130408,6.468269e-7,0.4720242,0.001470491,0.00006090301,0.000005798537,0.000130167,0.5145347,0.005162446,0.001628145,0.004231531,0.0003379718],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9369336,0.0007729004,0.05761777,0.001608641,0.0001861139,0.000184277,0.0006642081,0.00005399633,0.001978488],"genre_scores_gemma":[0.9747161,0.001154667,0.008854948,0.00004853334,0.00003446288,3.449122e-7,0.01493638,0.000009071301,0.0002455338],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5521629,"threshold_uncertainty_score":0.9896262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0241843875961516,"score_gpt":0.2218066483172283,"score_spread":0.1976222607210767,"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."}}