{"id":"W6991397592","doi":"","title":"GEOGRAPHIC INFORMATION SYSTEMS FOR ASSESSMENT OF CLIMATE CHANGE EFFECTS\\nON TEFF IN ETHIOPIA","year":2014,"lang":"en","type":"other","venue":"Bioline International (Bioline International)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"International Development Research Centre","keywords":"Climate change; Geographic information system; Information system; Geospatial analysis; Field (mathematics); Work (physics)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001709012,0.00101638,0.001308767,0.00533074,0.00005427125,0.0002044376,0.002010587,0.0009619577,0.0004611705],"category_scores_gemma":[0.0006773434,0.0009870515,0.00061471,0.0005469274,0.0001811917,0.0006268114,0.0004749504,0.0007142652,0.0005449012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007346087,"about_ca_system_score_gemma":0.0001792026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003229302,"about_ca_topic_score_gemma":0.0008114508,"domain_scores_codex":[0.9940736,0.0002087007,0.002446817,0.0008847205,0.001649969,0.0007361345],"domain_scores_gemma":[0.9938256,0.0005519768,0.003319272,0.0007420842,0.001383045,0.0001780164],"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":[0.00277987,0.005036066,0.1823218,0.01250827,0.009128994,0.00006217664,0.0007784449,0.004857577,0.004129723,0.3252991,0.4150385,0.03805946],"study_design_scores_gemma":[0.00558991,0.0002710797,0.01989586,0.004823757,0.0001300401,0.00002433164,0.00003659694,0.1038887,0.0001155521,0.0001870217,0.8639925,0.001044641],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.005231843,0.002856714,0.02709624,0.003438683,0.05430854,0.01915697,0.05206569,0.001859889,0.8339854],"genre_scores_gemma":[0.7621383,0.01545889,0.01248074,0.002013743,0.02801388,0.01277023,0.1098962,0.003588428,0.05363953],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7803459,"threshold_uncertainty_score":0.999258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01834437541851931,"score_gpt":0.3215602203818292,"score_spread":0.3032158449633099,"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."}}