{"id":"W1820453237","doi":"10.1111/cobi.12080","title":"How Good Science and Stories Can Go Hand‐In‐Hand","year":2013,"lang":"en","type":"article","venue":"Conservation Biology","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":39,"is_retracted":false,"has_abstract":false,"ca_institutions":"Saint Mary's University","funders":"University of Washington; David and Lucile Packard Foundation","keywords":"National Museum of Natural History; Art history; Art; Natural history; Humanities; Library science; Environmental ethics; Ecology; Philosophy; Biology; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001706496,0.00006457034,0.00007536257,0.00003134295,0.0002030916,0.000132087,0.0001087581,0.00004869432,0.003746303],"category_scores_gemma":[0.0001912307,0.00005468481,0.000007643253,0.00029087,0.001690912,0.0002130666,0.0000990085,0.00004302638,0.0001375238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002213896,"about_ca_system_score_gemma":0.00002142617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001606441,"about_ca_topic_score_gemma":0.004344264,"domain_scores_codex":[0.9994089,0.00002385503,0.00007926352,0.0002062422,0.00008553702,0.000196177],"domain_scores_gemma":[0.999723,0.00003352097,0.00003963528,0.0001031798,0.00003868661,0.0000619862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000002541848,0.00001400761,0.8107085,0.00000225314,0.000001162085,3.537963e-7,0.0002785719,1.396913e-7,0.1762876,0.006612088,0.004311939,0.001780833],"study_design_scores_gemma":[0.0001999409,0.00003479157,0.9058454,0.000001648741,0.000001283512,0.00000292604,0.000783927,0.00006672592,0.004238652,0.0004972595,0.08825211,0.00007534],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9805931,0.00004466832,0.00003261237,0.01461598,0.0001171033,0.0001315827,0.00001548367,0.00001234214,0.004437073],"genre_scores_gemma":[0.9978155,0.00003160022,0.00003196999,0.001235051,0.000009726389,0.00003157621,0.00002052272,0.000002233417,0.0008217591],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.172049,"threshold_uncertainty_score":0.9971644,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03402152749372529,"score_gpt":0.2455187267761963,"score_spread":0.211497199282471,"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."}}