{"id":"W3029151513","doi":"","title":"Private Fingerprint Matching.","year":2012,"lang":"en","type":"preprint","venue":"Research Online (University of Wollongong)","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Minutiae; Fingerprint (computing); Scalability; Protocol (science); Matching (statistics); Cryptography; Theoretical computer science; Modular design; Algorithm; Fingerprint recognition; Computer security; Mathematics; Programming language; Database","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":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.002640423,0.0002085276,0.0004120416,0.001705372,0.0003585781,0.0001571012,0.004465461,0.0003949535,0.0001759877],"category_scores_gemma":[0.0001688127,0.000255662,0.0002606063,0.002033935,0.0003460661,0.0004126623,0.008732171,0.001734214,0.0002022958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002626408,"about_ca_system_score_gemma":0.0004973464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001961831,"about_ca_topic_score_gemma":0.0002048418,"domain_scores_codex":[0.9964602,0.0004951728,0.00025487,0.0007498691,0.001387307,0.0006525833],"domain_scores_gemma":[0.9965796,0.0002389478,0.0002700202,0.001812248,0.0007405519,0.0003586418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0002041277,0.008530409,0.009455414,0.004054685,0.001246005,0.0004394781,0.04675497,0.000447098,0.006884824,0.449969,0.03922271,0.4327913],"study_design_scores_gemma":[0.002825664,0.0002929743,0.48658,0.001203888,0.0001325114,0.00004705315,0.004618168,0.06030953,0.001428937,0.0751295,0.3645208,0.002910979],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6246725,0.001105393,0.3603231,0.009815773,0.0008899746,0.0007886683,0.0002305925,0.0003172019,0.00185684],"genre_scores_gemma":[0.8788455,0.0008764361,0.1164264,0.00002926877,0.0001501441,9.527906e-7,0.000145151,0.00001787874,0.003508338],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4771246,"threshold_uncertainty_score":0.9999896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1097777900357687,"score_gpt":0.3484178450690851,"score_spread":0.2386400550333165,"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."}}