{"id":"W4408466346","doi":"10.5194/egusphere-egu25-16565","title":"Expanding Amazon dry-hot season under anthropogenic climate change","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Environmental science; Climate change; Evapotranspiration; Dry season; Amazon rainforest; Deforestation (computer science); Carbon sink; Global warming; Atmospheric sciences; Climatology; Wet season; Precipitation; Geography; Ecology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001283174,0.0001555521,0.0001780727,0.0001187501,0.0002917973,0.0003424525,0.0001995719,0.000198571,0.001173939],"category_scores_gemma":[0.0002734066,0.00007747314,0.0002228192,0.0002044781,0.0002251365,0.0003097461,0.000307795,0.000229055,0.00009687252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003800925,"about_ca_system_score_gemma":0.0003195885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01417496,"about_ca_topic_score_gemma":0.0171975,"domain_scores_codex":[0.9999329,0.000009366925,0.000003561164,0.0000203712,0.00001157647,0.00002227856],"domain_scores_gemma":[0.9998978,0.00001186301,0.00002857243,0.000009753531,0.00002311202,0.0000287498],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005481792,0.000293229,0.6851311,0.0003045835,0.0002889815,0.002174037,0.0007870906,0.04834018,0.215035,0.004172289,0.007213783,0.03571152],"study_design_scores_gemma":[0.00006057956,0.00009661375,0.9229084,0.00002162017,0.00009800267,0.0002848973,0.0008500328,0.0629959,0.005707207,0.0009318892,0.006014523,0.00003037843],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958025,0.0001483472,0.0009157507,0.0002300712,0.00002410191,0.000009307848,0.0004805666,0.00006643996,0.002322943],"genre_scores_gemma":[0.9994646,0.00006408613,0.0001618372,0.000049465,0.000006719817,0.000005002934,0.0001490252,0.000005397414,0.00009402665],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01417496,"threshold_uncertainty_score":0.02818495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0290697902046015,"score_gpt":0.2834481639978754,"score_spread":0.2543783737932739,"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."}}