{"id":"W3123398457","doi":"","title":"Crop productivity and adaptation to climate change in Pakistan","year":2015,"lang":"en","type":"preprint","venue":"London School of Economics and Political Science Research Online (London School of Economics and Political Science)","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Economic and Social Research Council; International Development Research Centre","keywords":"Climate change; Food security; Productivity; Adaptation (eye); Production (economics); Natural resource economics; Crop productivity; Agricultural economics; Business; Climate change adaptation; Environmental resource management; Crop; Agroforestry; Agricultural science; Geography; Economics; Agriculture; Environmental science; Economic growth; Forestry; 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":[0.0004758176,0.0001302398,0.0001333981,0.0003842375,0.0005059929,0.0008358422,0.0001539085,0.0002290708,0.00207556],"category_scores_gemma":[0.001281102,0.00008617855,0.0001652536,0.001197558,0.0005507872,0.0004499612,0.0005588292,0.0003088632,0.0002185292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001320886,"about_ca_system_score_gemma":0.0008317569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04640432,"about_ca_topic_score_gemma":0.05041365,"domain_scores_codex":[0.9997719,0.00004594879,0.000008684671,0.00003461114,0.00004149299,0.00009735479],"domain_scores_gemma":[0.9992589,0.0002543749,0.0002496147,0.00004571664,0.00009197705,0.00009948932],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001580011,0.000119901,0.9606883,0.00005272004,0.00007037378,0.0008862525,0.00130348,0.00951109,0.001137118,0.002495458,0.0009523156,0.02262507],"study_design_scores_gemma":[0.000006301606,0.00005680112,0.9948489,0.000006575884,0.000007575049,0.00006393061,0.001543936,0.001651533,0.0001428218,0.0005473359,0.001117921,0.000006314143],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970195,0.00006341648,0.0001366082,0.0001662563,0.000003229532,0.000003980341,0.000277999,0.000002315614,0.002326857],"genre_scores_gemma":[0.9995863,0.00009488173,0.00004090737,0.000006916132,0.000002130986,0.000001373199,0.00008515085,4.044933e-7,0.0001819737],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04640432,"threshold_uncertainty_score":0.09226847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1465281096686095,"score_gpt":0.3972522520740028,"score_spread":0.2507241424053933,"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."}}