{"id":"W2007189917","doi":"10.1038/npre.2009.3684.1","title":"Results of a Wildlife Toxicology Workshop held by Smithsonian Institution: Identification & Prioritization of Problem Statements","year":2009,"lang":"en","type":"preprint","venue":"Nature Precedings","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Wildlife; Population; Government (linguistics); Action (physics); Environmental planning; Prioritization; Geography; Engineering; Environmental health; Management science; Medicine; Ecology; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005978066,0.0002604361,0.0003619838,0.00008704065,0.00008037766,0.00004667838,0.0004828888,0.0009823834,0.001341579],"category_scores_gemma":[0.000347116,0.0002699053,0.0001046684,0.0004249755,0.0002380371,0.0002525738,0.0004430099,0.0007627912,0.00004738442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007767105,"about_ca_system_score_gemma":0.0000423821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001020924,"about_ca_topic_score_gemma":0.0003117893,"domain_scores_codex":[0.9975228,0.00007143319,0.0008668936,0.000621417,0.0006427428,0.0002747218],"domain_scores_gemma":[0.9982142,0.00004056557,0.001096318,0.0004256321,0.0001267303,0.00009652133],"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":[0.001207915,0.002289339,0.03318444,0.00130938,0.0002344863,0.000003286482,0.00594816,0.001932159,0.1212675,0.006282914,0.8042019,0.02213853],"study_design_scores_gemma":[0.006683343,0.0005909787,0.4062066,0.002470369,0.0004919768,0.00002015617,0.001718274,0.0005538877,0.130043,0.009572617,0.4391175,0.002531274],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9556548,0.0008129863,0.002993882,0.005674838,0.0013568,0.002262226,0.002616632,0.0001669986,0.02846081],"genre_scores_gemma":[0.9958341,0.0007410973,0.001046329,0.0003029753,0.00004837215,0.00005673761,0.001025783,0.00001581832,0.0009287494],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3730222,"threshold_uncertainty_score":0.9999753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02243374943034216,"score_gpt":0.3208191093139277,"score_spread":0.2983853598835856,"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."}}