{"id":"W2150280378","doi":"10.1038/nclimate1908","title":"The role of satellite remote sensing in climate change studies","year":2013,"lang":"en","type":"article","venue":"Nature Climate Change","topic":"Climate variability and models","field":"Environmental Science","cited_by":611,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"National Oceanic and Atmospheric Administration","keywords":"Climate change; Satellite; Remote sensing; Environmental science; Climate model; Temporal scales; Climatology; Earth system science; Scale (ratio); Meteorology; Geography; Geology; Oceanography; Cartography","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":[0.01777709,0.0005809948,0.0006751968,0.001914156,0.000611699,0.003419347,0.0009895274,0.001324671,0.004322563],"category_scores_gemma":[0.02562671,0.0003733864,0.0004425259,0.004872235,0.002782245,0.005866189,0.001737163,0.001830638,0.0003803185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001766564,"about_ca_system_score_gemma":0.00225489,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02606183,"about_ca_topic_score_gemma":0.03505747,"domain_scores_codex":[0.9954078,0.003561954,0.0000978929,0.0003226788,0.0005176213,0.00009203715],"domain_scores_gemma":[0.9590983,0.03460059,0.001578902,0.002248807,0.001780689,0.0006926111],"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":[0.0003924656,0.0002621867,0.1465592,0.002180069,0.0007022814,0.0001568126,0.001953757,0.04476018,0.002974453,0.2357882,0.0188028,0.5454677],"study_design_scores_gemma":[0.0001206523,0.0005174315,0.1356348,0.003521495,0.0005265813,0.0003574828,0.005454471,0.09928139,0.00345301,0.4332236,0.3177057,0.0002033835],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.223407,0.451483,0.09359425,0.1242986,0.003766023,0.00015103,0.003584415,0.0003104586,0.09940516],"genre_scores_gemma":[0.7825502,0.1759773,0.0293439,0.003167314,0.003416739,0.00006322723,0.0004598087,0.0001400983,0.00488145],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.02606183,"threshold_uncertainty_score":0.09401542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04300857450566189,"score_gpt":0.2877051942609736,"score_spread":0.2446966197553117,"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."}}