{"id":"W1896717591","doi":"10.1007/s10668-015-9710-6","title":"Is rainfall gradient a factor of livelihood diversification? Empirical evidence from around climatic hotspots in Indo-Gangetic Plains","year":2015,"lang":"en","type":"article","venue":"Environment Development and Sustainability","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"Calgary Laboratory Services","funders":"","keywords":"Livelihood; Diversification (marketing strategy); Geography; Agriculture; Climate change; Subsistence agriculture; Psychological resilience; Socioeconomics; Natural resource economics; Business; Ecology; Economics","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":[0.0006151687,0.0001952948,0.0002110208,0.001302721,0.0006299531,0.0008525025,0.0005030962,0.0002445243,0.002145843],"category_scores_gemma":[0.001901541,0.0001712224,0.0002981361,0.0025305,0.001383194,0.0006267396,0.0007110917,0.0003301423,0.0001215178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003358858,"about_ca_system_score_gemma":0.0003720641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01729415,"about_ca_topic_score_gemma":0.03017633,"domain_scores_codex":[0.9996792,0.0001198935,0.00002343249,0.00006662969,0.0000348416,0.00007604475],"domain_scores_gemma":[0.997376,0.0009462034,0.001044634,0.0001730795,0.0001699678,0.0002900655],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002827216,0.00001661263,0.9975055,0.000009276254,0.00005157288,0.00007161393,0.0006406688,0.00004810445,0.0001363706,0.00007555546,0.0000373858,0.001379111],"study_design_scores_gemma":[0.000001453453,0.000007176121,0.9981667,0.000005485357,0.00001830653,0.00002738283,0.001532628,0.00008313105,0.00001685415,0.00005205285,0.00008706702,0.000001672643],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993719,0.0001105942,0.00003299777,0.00005679237,0.000001799353,0.000001664412,0.00004529256,7.281908e-7,0.0003781927],"genre_scores_gemma":[0.9998199,0.00005638836,0.00001998587,0.000007949883,0.000004421929,0.000001205723,0.00004396277,4.598365e-7,0.00004563869],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01729415,"threshold_uncertainty_score":0.03438699,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1197218329269702,"score_gpt":0.2788853344328469,"score_spread":0.1591635015058767,"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."}}