{"id":"W4392714453","doi":"10.1016/j.heliyon.2024.e28003","title":"Rural households' livelihood adaptation strategies in the face of changing climate: A case study from Pakistan","year":2024,"lang":"en","type":"article","venue":"Heliyon","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"King Saud University","keywords":"Livelihood; Agriculture; Vulnerability (computing); Diversification (marketing strategy); Business; Climate change; Multistage sampling; Socioeconomics; Geography; Agricultural diversification; Agricultural economics; Natural resource economics; Economics; Marketing","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":[],"consensus_categories":[],"category_scores_codex":[0.0003576285,0.0001496144,0.0001564205,0.00002344872,0.0001172485,0.0002658645,0.0001703431,0.00007163961,0.00009116851],"category_scores_gemma":[0.00001412274,0.00004500728,0.00006036252,0.0007082928,0.00002219187,0.0002578076,0.00005892759,0.0001607064,0.00001660637],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003169573,"about_ca_system_score_gemma":0.000006819944,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002772187,"about_ca_topic_score_gemma":0.02366534,"domain_scores_codex":[0.9988601,0.0001366345,0.0002401821,0.00020998,0.0002376133,0.0003154876],"domain_scores_gemma":[0.9995277,0.0002822387,0.00006053186,0.00006215219,0.00003085533,0.00003652846],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.000170449,0.001844538,0.0200463,0.0005912127,0.0001183442,0.007264823,0.5470081,0.0002850308,0.3146597,0.0008029056,0.0002595042,0.1069492],"study_design_scores_gemma":[0.0001269151,0.0003596794,0.06516048,0.0002873745,0.00002645097,0.0001385349,0.9331492,0.0001939508,0.0002386052,0.00004383412,0.0001354763,0.0001394751],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995516,0.002827955,0.000003194562,0.0005812446,0.0001119612,0.0004810017,0.0002785017,0.00009270537,0.0001074471],"genre_scores_gemma":[0.9991417,0.0004892707,0.000009909547,0.00006262091,0.0001763538,0.00003233073,0.00007678661,0.000001625021,0.000009429777],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3861412,"threshold_uncertainty_score":0.9941502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05331486249118236,"score_gpt":0.2946108630747408,"score_spread":0.2412960005835585,"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."}}