{"id":"W1751789849","doi":"","title":"NOAA AVHRR Data Curation and Reprocessing - TIMELINE","year":2013,"lang":"en","type":"article","venue":"elib (German Aerospace Center)","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Advanced very-high-resolution radiometer; Thematic map; Remote sensing; Earth observation; Timeline; Environmental science; Thematic Mapper; Ancillary data; Ground segment; Meteorology; Data archive; Land cover; Geography; Database; Computer science; Satellite imagery; Cartography; Satellite; Land use; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004710889,0.001109234,0.001184128,0.004344224,0.001904709,0.00388449,0.002369103,0.000872227,0.04269535],"category_scores_gemma":[0.009347042,0.000673869,0.001150392,0.005886518,0.0006831836,0.002337601,0.002998,0.002062748,0.06016779],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001943006,"about_ca_system_score_gemma":0.01382131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07519907,"about_ca_topic_score_gemma":0.06801329,"domain_scores_codex":[0.995351,0.0004769926,0.0004712242,0.0007166515,0.002686443,0.0002977827],"domain_scores_gemma":[0.9831772,0.0007120749,0.0008982823,0.00375975,0.01068459,0.0007681397],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001058061,0.00005163786,0.00160633,0.0003993145,0.00003210533,0.00009604169,0.0002217231,0.0005757484,0.003452118,0.002133296,0.9163124,0.07501343],"study_design_scores_gemma":[0.00001862026,0.00001247224,0.003617759,0.0001065556,0.000008443713,0.00003067623,0.0000797168,0.0004071398,0.001935504,0.0007263543,0.9930327,0.00002411583],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.00382451,0.0006993941,0.05629534,0.001839717,0.003041436,0.001534494,0.8627258,0.02033272,0.04970659],"genre_scores_gemma":[0.004144439,0.0004847189,0.07181524,0.0004135015,0.0002138964,0.001005407,0.8975228,0.006148752,0.01825118],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.07519907,"threshold_uncertainty_score":0.1495227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03296801637479127,"score_gpt":0.2580763978113393,"score_spread":0.225108381436548,"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."}}