{"id":"W2347125256","doi":"10.1088/1748-9326/11/5/054006","title":"Measuring and tracking the flow of climate change adaptation aid to the developing world","year":2016,"lang":"en","type":"article","venue":"Environmental Research Letters","topic":"International Development and Aid","field":"Social Sciences","cited_by":133,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"University of British Columbia","keywords":"Climate Finance; Adaptation (eye); Climate change; Developing country; Climate change adaptation; Relevance (law); Tracking (education); Development aid; Environmental resource management; Finance; Economics; Political science; Economic growth; Sociology; Ecology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001885775,0.000047504,0.00004293963,0.00008206393,0.0006051253,0.00004670435,0.0002252331,0.00001229432,0.00008024264],"category_scores_gemma":[0.0001104388,0.00002522408,0.00001763293,0.0001272243,0.0002835394,0.0002007988,0.0001283732,0.00008006742,0.00006399818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002072533,"about_ca_system_score_gemma":0.00001430239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001094387,"about_ca_topic_score_gemma":0.0007505701,"domain_scores_codex":[0.9985126,0.0002207211,0.00009959882,0.0001216865,0.0007670425,0.0002783545],"domain_scores_gemma":[0.9995279,0.0003279386,0.00002700589,0.00006794857,0.000009847013,0.000039336],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00009056875,0.00003030196,0.06578904,0.00001479535,0.0000448598,0.000007963817,0.08562759,0.00002983334,0.04245425,0.02122435,0.001263406,0.7834231],"study_design_scores_gemma":[0.0004399934,0.00003451454,0.8242748,0.0003796833,0.000005498998,0.000001109582,0.01087388,0.0001085607,0.008731817,0.0009737123,0.1539279,0.0002484874],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7970563,0.0000915352,0.0005637562,0.1996935,0.0001350608,0.0004537101,0.000007519605,0.000008912727,0.001989654],"genre_scores_gemma":[0.9976436,0.0004160319,0.0004745072,0.0009707108,0.0001765182,0.00004980512,7.772853e-7,0.000005896698,0.0002621138],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7831746,"threshold_uncertainty_score":0.4654196,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.169685265578523,"score_gpt":0.3403148003011711,"score_spread":0.170629534722648,"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."}}