{"id":"W3129710742","doi":"","title":"Synthesis and key insights from the implementation of the gender sensitive Climate-Smart Agriculture monitoring framework in Central America: temporal and spatial dynamics in the Olopa (Guatemala) and Santa Rita (Honduras) Climate Smart Villages","year":2020,"lang":"en","type":"article","venue":"CGSPace A Repository of Agricultural Research Outputs (Consultative Group for International Agricultural Research)","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Consortium of International Agricultural Research Centers; International Development Research Centre","keywords":"Agriculture; Geography; Climate change; Key (lock); Environmental resource management; Regional science; Climatology; Environmental planning; Ecology; Environmental science; Archaeology","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":[0.004162072,0.0004746787,0.0005441253,0.002184175,0.001076941,0.0029737,0.00107291,0.0006033191,0.002531858],"category_scores_gemma":[0.008023318,0.0002211984,0.000519171,0.006583881,0.001785669,0.001885756,0.00296514,0.00092884,0.0001158629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007138682,"about_ca_system_score_gemma":0.006222731,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2584232,"about_ca_topic_score_gemma":0.2737929,"domain_scores_codex":[0.9982527,0.0007283444,0.00009678661,0.000282221,0.0001818689,0.0004582018],"domain_scores_gemma":[0.993013,0.004088205,0.001305823,0.0004169289,0.0008945395,0.0002815008],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004529651,0.0002829514,0.5342803,0.003351622,0.0006732292,0.00248068,0.3097375,0.006116242,0.003709521,0.02139127,0.00898474,0.108539],"study_design_scores_gemma":[0.00001338992,0.0001239681,0.7088644,0.00130667,0.0002016826,0.00009244363,0.264225,0.001873,0.0006290376,0.002464122,0.0201559,0.00005045129],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.979026,0.00317159,0.001826119,0.004684404,0.00006278745,0.0001365812,0.003088245,0.00002010108,0.007984173],"genre_scores_gemma":[0.9960546,0.001178233,0.001023415,0.0003593192,0.00002021713,0.0001069123,0.0008237933,0.00000940522,0.000424045],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2584232,"threshold_uncertainty_score":0.513838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06453699129009463,"score_gpt":0.3348895264493723,"score_spread":0.2703525351592776,"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."}}