{"id":"W6926154085","doi":"10.21223/p3/czkanf/fw2wjt","title":"Data Dictionary - A4 - Monitoring Agricultural Activities by CIP agronomist.docx","year":2018,"lang":"en","type":"dataset","venue":"International Potato Center","topic":"History of Computing Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Global Health Research","funders":"","keywords":"Agriculture; Agricultural productivity; Work (physics); Information system; Expert system","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":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0001930022,0.0004346695,0.0003072244,0.0002779182,0.0002237003,0.0004720532,0.009370775,0.000265073,0.0001146369],"category_scores_gemma":[0.00009031792,0.0004046985,0.0001157451,0.0001298038,0.0002239485,0.001322326,0.004632121,0.0005707082,0.0003921669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005044244,"about_ca_system_score_gemma":0.0000865377,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001001514,"about_ca_topic_score_gemma":0.00001788347,"domain_scores_codex":[0.9972363,0.00006088679,0.0004547609,0.001067677,0.0007746376,0.0004057732],"domain_scores_gemma":[0.9973212,0.0001270582,0.0004019556,0.001935679,0.0001208041,0.00009324114],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007073347,0.0001192769,0.00008087282,0.00001255669,0.0001493597,0.00002137659,0.00002737805,0.000002472594,0.00003612805,0.00005322623,0.9985002,0.0009900889],"study_design_scores_gemma":[0.0002348814,0.0000416344,0.0003823416,0.0001298896,0.00001305298,0.00007957489,0.00001799049,0.000261103,0.0001172412,0.0001221176,0.9981863,0.0004138155],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0007702233,0.0002177977,0.002449867,0.001399244,0.01279954,0.0001473583,0.9811985,0.0005430028,0.0004744132],"genre_scores_gemma":[0.001613722,0.0001001906,0.004516592,0.000172299,0.001789512,0.00002493896,0.9907025,0.00002113405,0.001059116],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01101003,"threshold_uncertainty_score":0.9998405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02597095058803245,"score_gpt":0.2750696042638275,"score_spread":0.2490986536757951,"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."}}