{"id":"W2013831057","doi":"10.1111/j.1442-9993.2007.01773.x","title":"Australia's Mammal Extinctions: A 50 000 Year History","year":2007,"lang":"en","type":"article","venue":"Austral Ecology","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":247,"is_retracted":false,"has_abstract":false,"ca_institutions":"Department of Environment and Conservation","funders":"","keywords":"Citation; Lynch syndrome; Mammal; History; Geography; Genealogy; Ecology; Library science; Computer science; Biology","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":["insufficient_payload"],"category_scores_codex":[0.0003818688,0.0001067073,0.0001132904,0.00004537623,0.00009600937,0.000003791154,0.0001567976,0.0002388194,0.08282024],"category_scores_gemma":[0.00004524713,0.0001147128,0.00004663312,0.00008925358,0.0003153577,0.0001568854,0.00006447746,0.0002172859,0.006105019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005667624,"about_ca_system_score_gemma":0.00001937026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004757128,"about_ca_topic_score_gemma":0.003739272,"domain_scores_codex":[0.9989606,0.00004628039,0.0002205903,0.0002613628,0.00009144816,0.0004196775],"domain_scores_gemma":[0.9995658,0.00008832655,0.00007630009,0.0001637684,0.00000642741,0.00009937151],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003994395,0.00007079333,0.9386477,0.000001341889,0.00000926631,0.00003069616,0.00006269116,0.00006284718,0.0004052871,0.0008996311,0.0592556,0.0005141796],"study_design_scores_gemma":[0.0002311916,0.0001177035,0.8612087,5.767678e-7,0.0000122632,0.00003172332,0.00004787686,0.000007543325,0.00004774647,0.0004157083,0.1377716,0.0001073059],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9748335,0.000003144161,0.00009985676,0.0006247242,0.0009082174,0.0001289682,0.000001583339,0.00005861135,0.02334141],"genre_scores_gemma":[0.9676909,0.000002296874,0.0009048941,0.001044374,0.0001249932,0.00001681246,0.00000816279,0.000008123869,0.0301994],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07851601,"threshold_uncertainty_score":0.9946688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02875961238555081,"score_gpt":0.2514060235165692,"score_spread":0.2226464111310184,"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."}}