{"id":"W7030511175","doi":"","title":"Cold Front","year":2008,"lang":"en","type":"other","venue":"RMIT Research Repository (RMIT University Library)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Population; Circumstantial evidence; Limiting; Gloom; Filter (signal processing)","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","research_integrity","insufficient_payload"],"consensus_categories":["research_integrity","insufficient_payload"],"category_scores_codex":[0.000376417,0.0008708424,0.001015168,0.004103034,0.001243026,0.0003124269,0.003348967,0.001454949,0.006012068],"category_scores_gemma":[0.00008052769,0.001019042,0.0005517395,0.001842804,0.001795202,0.001356594,0.001978306,0.002931922,0.02485672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001067375,"about_ca_system_score_gemma":0.002404187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004183574,"about_ca_topic_score_gemma":0.0002507392,"domain_scores_codex":[0.9904832,0.002349583,0.0004119757,0.001886644,0.002940915,0.001927663],"domain_scores_gemma":[0.9951173,0.0003676242,0.0004116086,0.002614376,0.0002250608,0.001264004],"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":[0.0002625997,0.0003649752,0.002902633,0.0001804663,0.0004540904,0.01325231,0.0001158669,0.000001973022,0.0009615514,0.002132238,0.9792935,0.00007776021],"study_design_scores_gemma":[0.001174515,0.0001925212,0.0006204322,0.0005141468,0.0000694321,0.00008446159,0.0002240475,0.00002147099,0.003395171,0.00001663199,0.9927085,0.0009786818],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0007270692,0.002441344,0.00001106462,0.0002180575,0.0006109367,0.001521908,0.0006345545,0.003085053,0.99075],"genre_scores_gemma":[0.001178326,0.001229411,0.00093315,0.00003280972,0.001560443,0.000007505092,0.0002296757,0.002516937,0.9923117],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.01884465,"threshold_uncertainty_score":0.9998414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03217162731251171,"score_gpt":0.2476592460594496,"score_spread":0.2154876187469379,"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."}}