{"id":"W4253362786","doi":"10.1016/s0959-3780(04)00048-2","title":"","year":2004,"lang":"en","type":"article","venue":"Global Environmental Change","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University; United Nations University Institute for Water, Environment, and Health","funders":"","keywords":"Computer science","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002192818,0.000645068,0.0003938269,0.00006332203,0.0003426679,0.0000657096,0.0006424375,0.0001861477,0.00016944],"category_scores_gemma":[0.00001338049,0.0006884428,0.0002487764,0.0004499033,0.0005652066,0.001425468,0.0005962263,0.0001983066,0.009500219],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006200296,"about_ca_system_score_gemma":0.0000153183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001882709,"about_ca_topic_score_gemma":0.0004264678,"domain_scores_codex":[0.9958502,0.00007760619,0.000437285,0.001030032,0.001157191,0.001447679],"domain_scores_gemma":[0.9983013,0.000008275347,0.0001827062,0.0008091711,0.000003009844,0.0006955773],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008245742,0.004204204,0.8596919,0.00002583673,0.0001901948,0.001077085,0.003742937,0.001159312,0.1113949,0.00637675,0.0001098527,0.01120247],"study_design_scores_gemma":[0.006984435,0.0005267237,0.9750578,0.00003275931,0.00006685752,0.000512822,0.001213014,0.00001607219,0.006904881,0.005240709,0.002519576,0.0009243347],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926875,0.001012743,0.00009024345,0.0009701407,0.0002414964,0.001186392,0.002600868,0.0005643875,0.0006462747],"genre_scores_gemma":[0.9948138,0.00006596416,0.001061071,0.002821445,0.0004127367,0.0004224678,0.0002989109,0.00009643099,0.000007190184],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.115366,"threshold_uncertainty_score":0.9995567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02929900452707248,"score_gpt":0.2344504367121106,"score_spread":0.2051514321850381,"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."}}