{"id":"W4388679271","doi":"10.55161/svvo2555","title":"NINE WAYS TO AVOID THE AMAZON TIPPING POINT","year":2023,"lang":"en","type":"report","venue":"","topic":"Ecosystem dynamics and resilience","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Universidade do Estado do Amazonas","keywords":"Tipping point (physics); Amazon rainforest; Deforestation (computer science); Climate change; Geography; Amazonian; Natural resource economics; Greenhouse gas; Global warming; Environmental resource management; Environmental science; Agroforestry; Ecology; Economics; Computer science","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001248527,0.0002362347,0.0002673103,0.00004977315,0.0002652058,0.00007197403,0.0006718123,0.0001568219,0.003219417],"category_scores_gemma":[0.000164321,0.0001328585,0.0001291351,0.0003951039,0.00007730025,0.00004696521,0.0008808055,0.0002984372,0.008921658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005533781,"about_ca_system_score_gemma":0.00006634993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005701011,"about_ca_topic_score_gemma":0.008411397,"domain_scores_codex":[0.9976524,0.00002334689,0.0003757661,0.0005430161,0.0009999737,0.0004055333],"domain_scores_gemma":[0.9989407,0.00009376468,0.0001415173,0.0006635182,0.00002001114,0.0001404955],"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":[0.00000687643,0.00006271559,0.007994917,0.0002725516,0.00007326941,0.0001548048,0.0005875038,0.01170007,0.002319374,0.0006864484,0.9602482,0.01589327],"study_design_scores_gemma":[0.0001384772,0.0001514541,0.03398488,0.000679484,0.00005729144,0.0001819111,0.0004636286,0.01083864,0.000210427,0.0006300451,0.951569,0.001094783],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.008054139,0.00007499762,0.003913623,0.00182411,0.001997809,0.0007371215,0.00002785871,0.0001851248,0.9831852],"genre_scores_gemma":[0.313018,0.001633111,0.001238113,0.001200652,0.0009339908,0.0002099943,0.00006623092,0.00018888,0.681511],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3049639,"threshold_uncertainty_score":0.9976918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05452167966492889,"score_gpt":0.2895604122045473,"score_spread":0.2350387325396184,"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."}}