{"id":"W3180893688","doi":"10.1109/crv52889.2021.00027","title":"To Keystone or Not to Keystone, that is the Correction","year":2021,"lang":"en","type":"article","venue":"","topic":"Image and Object Detection Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Keystone species; Computer science; Leverage (statistics); Perspective (graphical); Computer vision; Artificial intelligence; Signage; Advertising","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":[],"consensus_categories":[],"category_scores_codex":[0.0002313555,0.0001172868,0.000119866,0.0001081665,0.0002206628,0.0002872226,0.0005114758,0.00004943034,0.0003827326],"category_scores_gemma":[0.00009361387,0.0000748509,0.00006753365,0.0009965146,0.00001335066,0.000285616,0.0003414425,0.0001192294,0.0006385848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006619278,"about_ca_system_score_gemma":0.00007878191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003189853,"about_ca_topic_score_gemma":0.0002791772,"domain_scores_codex":[0.9988879,0.00006296908,0.0001428545,0.0003870006,0.0002903624,0.0002289189],"domain_scores_gemma":[0.9988817,0.00008755507,0.00003004337,0.0007359441,0.0001650105,0.00009974798],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004627006,0.00006314537,0.00003047623,0.000007018074,0.00002097181,0.00006441117,0.003486215,0.00001490275,0.02565276,0.0007982432,0.4546299,0.5151857],"study_design_scores_gemma":[0.00005403408,0.0001199431,0.000780036,0.00001150069,0.000003538402,0.00009096178,0.000207786,0.0007233452,0.9065211,0.000102472,0.09125552,0.0001297379],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004264049,0.00001314723,0.9675848,0.01410167,0.001459672,0.0002489731,9.016812e-7,0.0006138251,0.01171299],"genre_scores_gemma":[0.6829436,0.00002384237,0.06335804,0.07932682,0.0002017275,0.0001025269,7.532763e-7,0.00001942455,0.1740232],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9042267,"threshold_uncertainty_score":0.8207928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02385351018283622,"score_gpt":0.2871127725504403,"score_spread":0.2632592623676041,"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."}}