{"meta":{"query_hash":"66812501f58b","filters":{"venue":"Xingshi jishu"},"cohort_total":1,"direct_labels_cover":0,"predictions_cover":1,"exported":1,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/66812501f58b","api":"https://metacan.xera.ac/api/v1/cohort?venue=Xingshi+jishu"},"results":[{"id":"W2347737370","doi":"","title":"Study on Fingerprint Examiner's Stability of Feature Selection","year":2015,"lang":"en","type":"article","venue":"Xingshi jishu","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Science North","funders":"","keywords":"Minutiae; Fingerprint (computing); Fingerprint recognition; Computer science; Pattern recognition (psychology); Identification (biology); Artificial intelligence; Selection (genetic algorithm); Stability (learning theory); Feature selection; Data mining; Quality (philosophy); Machine learning; Biology","score_opus":0.09118403537136523,"score_gpt":0.2962402244164011,"score_spread":0.20505618904503586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2347737370","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9759532,0.000028567434,0.02024837,0.0005049893,0.00044315628,0.00025061786,0.0000022376732,0.00012780065,0.002441048],"genre_scores_gemma":[0.99716187,5.5589425e-7,0.0025316204,0.00006645448,0.000032861462,0.000008695431,0.0000017745573,0.0000037255018,0.0001924606],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99883467,0.00011951764,0.00017439233,0.00032466205,0.0004167535,0.0001300188],"domain_scores_gemma":[0.9990155,0.00006059572,0.000110765046,0.00046594886,0.0002562218,0.00009097998],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009277895,0.00008476329,0.00012934569,0.00020478698,0.000048269572,0.000089494024,0.0004559,0.000057707177,0.000009582671],"category_scores_gemma":[0.0003603296,0.00007652389,0.000035961744,0.0013109854,0.00002399117,0.00019360305,0.00012128555,0.00015029969,0.000029753744],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001630402,0.011485912,0.6582348,0.00013490728,0.00019579567,0.000032655324,0.08894869,0.00009783548,0.014741394,0.04518192,0.062402796,0.11838029],"study_design_scores_gemma":[0.0012903853,0.0011682963,0.93081754,0.000019041121,0.0000150013675,0.000010060808,0.0018885676,0.00483014,0.045053627,0.001466894,0.013052234,0.00038823325],"about_ca_topic_score_codex":0.00008450824,"about_ca_topic_score_gemma":0.000028621278,"teacher_disagreement_score":0.27258277,"about_ca_system_score_codex":0.000087895954,"about_ca_system_score_gemma":0.00006925378,"threshold_uncertainty_score":0.31205535},"labels":[],"label_agreement":null}]}