{"id":"W4292316413","doi":"10.3390/su141610196","title":"Impact of Farmers’ Climate Risk Perception and Socio-Economic Attributes on Their Choice of ICT-Based Agricultural Information Services: Empirical Evidence from Pakistan","year":2022,"lang":"en","type":"article","venue":"Sustainability","topic":"Agricultural Innovations and Practices","field":"Agricultural and Biological Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Information and Communications Technology; Multivariate probit model; Business; Agricultural extension; Cropping; Agriculture; Multistage sampling; Marketing; Population; Risk perception; Socioeconomics; Perception; Geography; Economics; Political science; Psychology; Environmental health","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":[0.0006359749,0.0001614551,0.0002368469,0.00001953788,0.0004589084,0.00005975566,0.000204928,0.00006948681,0.0005572235],"category_scores_gemma":[0.0001726283,0.00005797224,0.0001552565,0.0003471888,0.0001000973,0.0008274932,0.0001334057,0.0002122073,0.000002181461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006104996,"about_ca_system_score_gemma":0.00005178535,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01385837,"about_ca_topic_score_gemma":0.0003442387,"domain_scores_codex":[0.9985542,0.0003556623,0.0004565887,0.0002334252,0.0001877551,0.0002123411],"domain_scores_gemma":[0.9976317,0.001195964,0.0006006747,0.00009080079,0.0004282196,0.00005261913],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002261898,0.0001181539,0.9790153,0.00005642765,0.00002644596,1.083784e-7,0.001585111,0.001131246,0.00534529,0.00002899447,0.0001092588,0.0123575],"study_design_scores_gemma":[0.0001400611,0.0007889055,0.9704816,0.00001236278,0.00002271318,5.049897e-7,0.02713313,0.0004386753,0.0001177439,0.0002824347,0.0004526218,0.0001292267],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967071,0.00005319938,0.000002613461,0.001450866,0.00003545855,0.0003781415,0.001319473,0.00002826415,0.00002486561],"genre_scores_gemma":[0.9991815,0.00004010038,0.00002503601,0.0000539227,0.00004261977,0.00003208969,0.0006204736,5.809189e-7,0.000003691551],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02554802,"threshold_uncertainty_score":0.9927084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0376400984479725,"score_gpt":0.3214277787349554,"score_spread":0.2837876802869829,"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."}}