{"id":"W7002023373","doi":"","title":"Mapping vegetation phenology in the Sahel and Soudan, Africa, 1982 to 2005","year":2006,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Data Analysis with R","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Oceanic and Atmospheric Administration; Lunds Universitet; Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Phenology; Vegetation (pathology); Precipitation; Climate change; Ecosystem; Tropical vegetation","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0001832538,0.0001689782,0.0001102677,0.001046497,0.0002228623,0.0003170357,0.0001120187,0.00008448913,0.000475321],"category_scores_gemma":[0.0005085405,0.00007204607,0.00008841051,0.001299151,0.00008371385,0.0001729602,0.0002301738,0.00007681239,0.0001127284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006049463,"about_ca_system_score_gemma":0.0004522841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05964281,"about_ca_topic_score_gemma":0.1417219,"domain_scores_codex":[0.9999522,0.000006836501,0.00000334359,0.00001349772,0.00001022764,0.00001389914],"domain_scores_gemma":[0.9998052,0.00002560454,0.00005814384,0.000006856892,0.00006581275,0.00003847092],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000219625,0.00003778092,0.91128,0.0002430179,0.00008406223,0.0003123347,0.002780507,0.0013499,0.006416209,0.0002164464,0.002304775,0.07475533],"study_design_scores_gemma":[0.000004044313,0.00001368247,0.9962125,0.00001820779,0.000008445247,0.00003653031,0.0005570388,0.0003728731,0.0003435666,0.00001332021,0.002417575,0.000002242805],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953311,0.0003985463,0.0001451123,0.00004105255,0.000005507829,0.00001094341,0.002637953,0.00001441973,0.001415296],"genre_scores_gemma":[0.9948606,0.0007141938,0.0008727317,0.00001706851,0.000009110274,0.00002914912,0.002783236,0.000005263885,0.00070857],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05964281,"threshold_uncertainty_score":0.1185913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01699110341403247,"score_gpt":0.2368170817335501,"score_spread":0.2198259783195177,"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."}}