{"id":"W2908717718","doi":"10.5751/es-10623-240105","title":"Smallholder farmers&amp;#8217; social networks and resource-conserving agriculture in Ghana: a multicase comparison using exponential random graph models","year":2019,"lang":"en","type":"article","venue":"Ecology and Society","topic":"Energy and Environment Impacts","field":"Environmental Science","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Exponential random graph models; Agriculture; Exponential function; Graph; Enumeration; Resource (disambiguation); Mathematics; Agricultural science; Computer science; Geography; Random graph; Environmental science; Ecology; Discrete mathematics; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.000342915,0.000166999,0.0002740401,0.00001429578,0.0003455768,0.00002559361,0.00008188508,0.0003446215,0.0003203554],"category_scores_gemma":[0.00000686914,0.0001465126,0.00008552078,0.0001046457,0.0002925449,0.0001820621,0.0002061018,0.000319026,0.000008956491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007192542,"about_ca_system_score_gemma":0.000004102609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002999454,"about_ca_topic_score_gemma":0.0005709544,"domain_scores_codex":[0.9988409,0.0001428018,0.0001983467,0.0003340608,0.0001009165,0.0003830308],"domain_scores_gemma":[0.9996203,0.0001153065,0.00007635127,0.00009242102,0.000001837814,0.00009384163],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001708358,0.0002347063,0.4993083,0.00002065768,0.00008839797,0.000008674463,0.01299294,0.4804024,0.004176405,0.00010709,0.002025084,0.0004645416],"study_design_scores_gemma":[0.005167959,0.00006468,0.8204057,0.00001921625,0.00008308725,0.00002846073,0.006548015,0.1660724,0.00004527671,0.0002882242,0.0007887667,0.0004881426],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976526,0.0001685548,0.0008865839,0.0001930297,0.00006811465,0.000189126,0.000001924293,0.00001598968,0.0008240379],"genre_scores_gemma":[0.9978822,0.00007407778,0.001046474,0.0007290647,0.00003848881,0.000007687108,0.0000118375,0.000009865488,0.0002003266],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3210974,"threshold_uncertainty_score":0.5974612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01949785872360159,"score_gpt":0.2287680741108775,"score_spread":0.2092702153872759,"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."}}