{"id":"W2106879375","doi":"10.1038/nclimate1934","title":"Clouds and temperature drive dynamic changes in tropical flower production","year":2013,"lang":"en","type":"article","venue":"Nature Climate Change","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":84,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"National Oceanic and Atmospheric Administration","keywords":"Environmental science; Precipitation; Tropics; Tropical and subtropical dry broadleaf forests; Climate change; Productivity; Tropical forest; Primary production; Tropical climate; Ecosystem; Atmospheric sciences; Ecology; Climatology; Agroforestry; Geography; Biology; Meteorology","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":[0.0000515747,0.0001364196,0.0001605934,0.00001482693,0.0001308216,0.00004639748,0.00007821532,0.0002573199,0.0001127768],"category_scores_gemma":[0.00002812072,0.00004913762,0.00002502945,0.0001880225,0.00004208117,0.0001233532,0.00007593165,0.0003354612,0.00002645859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001933177,"about_ca_system_score_gemma":6.204552e-7,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000375319,"about_ca_topic_score_gemma":0.02106515,"domain_scores_codex":[0.9992173,0.0000262303,0.00008112743,0.0002845992,0.0001042752,0.0002864933],"domain_scores_gemma":[0.9998299,0.00003316199,0.00003049442,0.00001845659,0.00003989719,0.00004803169],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00007309111,0.0001323247,0.2174477,0.00006129167,0.00001459575,0.00002107013,0.0007898815,3.555447e-8,0.7403494,0.0003661794,0.002571057,0.03817343],"study_design_scores_gemma":[0.00007329317,0.00009852798,0.9954952,0.00005170379,0.000004230082,0.000009936765,0.0004958101,0.00001192668,0.0006442922,0.0001010584,0.002875216,0.0001387795],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9812631,0.002391136,1.997039e-9,0.01553384,0.0001966508,0.0003247374,0.00004276751,0.00004951768,0.0001982783],"genre_scores_gemma":[0.9953343,0.00315674,0.00001204858,0.0005957313,0.0006919502,0.00008429911,0.00003652378,0.00000104306,0.00008733411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7780475,"threshold_uncertainty_score":0.9967979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02200824057376799,"score_gpt":0.221561039748966,"score_spread":0.199552799175198,"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."}}