{"id":"W3008770712","doi":"10.1007/s40641-020-00153-z","title":"Migration and Household Adaptation in Climate-Sensitive Hotspots in South Asia","year":2020,"lang":"en","type":"article","venue":"Current Climate Change Reports","topic":"Climate Change, Adaptation, Migration","field":"Social Sciences","cited_by":119,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Department for International Development; International Development Research Centre","keywords":"Livelihood; Climate change; Diversification (marketing strategy); Adaptive capacity; South asia; Development economics; Context (archaeology); Geography; Natural resource economics; Climate change adaptation; Business; Adaptive strategies; Environmental resource management; Economic growth; Economics; Agriculture; Ecology","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":[0.0008611431,0.0004280046,0.0007675121,0.001520309,0.0003815248,0.001343213,0.0006196112,0.000567555,0.002858293],"category_scores_gemma":[0.003369412,0.0001704648,0.0008083188,0.002930228,0.0005908101,0.001194875,0.0009616989,0.0007472663,0.000179441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008498605,"about_ca_system_score_gemma":0.00292347,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01469071,"about_ca_topic_score_gemma":0.01441932,"domain_scores_codex":[0.9996345,0.000144646,0.00006764844,0.00005773468,0.00005733742,0.00003813832],"domain_scores_gemma":[0.9983627,0.0008266406,0.0004924922,0.0000328116,0.0002141563,0.00007123451],"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":[0.0002534612,0.0001628982,0.06569295,0.1971928,0.002384049,0.00128169,0.009149904,0.0026685,0.0006322487,0.007850061,0.0110784,0.701653],"study_design_scores_gemma":[0.00006120185,0.0006006162,0.4786129,0.1919235,0.004713392,0.002795654,0.02867815,0.00118598,0.0008204734,0.004866156,0.2855884,0.0001535671],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.0267878,0.9678403,0.0002673618,0.001840645,0.0003753024,0.00004724561,0.000195114,0.000007261723,0.002639062],"genre_scores_gemma":[0.1283243,0.8703575,0.0002716628,0.0003826794,0.0002332892,0.00005055076,0.0001007335,0.000002476702,0.0002769603],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01469071,"threshold_uncertainty_score":0.02921045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2890365306061172,"score_gpt":0.3440211031227572,"score_spread":0.05498457251664002,"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."}}