{"meta":{"query_hash":"8ca2b9a07b2c","filters":{"venue":"BIOCOMP"},"cohort_total":2,"direct_labels_cover":0,"predictions_cover":2,"exported":2,"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/8ca2b9a07b2c","api":"https://metacan.xera.ac/api/v1/cohort?venue=BIOCOMP"},"results":[{"id":"W17603131","doi":"10.1123/jab.23.2.119","title":"Long spaced seeds for finding similarities between biological sequences.","year":2007,"lang":"en","type":"article","venue":"BIOCOMP","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Sensitivity (control systems); Homology (biology); Measure (data warehouse); Mathematics; Algorithm; Fraction (chemistry); Computer science; Biology; Data mining; Genetics; Gene","score_opus":0.07917843696535799,"score_gpt":0.31957608837918283,"score_spread":0.24039765141382485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W17603131","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07064436,0.00017590933,0.9276822,0.00036035944,0.0003138555,0.00023050999,0.000027952045,0.00017835436,0.0003864919],"genre_scores_gemma":[0.81912667,0.000009467739,0.18003972,0.00019213109,0.00043315542,0.000010842092,0.00004484503,0.0000069038265,0.0001362918],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99885774,0.00002318469,0.00021152437,0.0003496317,0.00016628182,0.00039163974],"domain_scores_gemma":[0.9991377,0.00030176714,0.00007494559,0.0003260147,0.000049450744,0.000110109686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057673967,0.00013400333,0.00018388177,0.00009569863,0.00023120314,0.00013691056,0.0007410677,0.00011567555,0.000009906887],"category_scores_gemma":[0.0000339257,0.0001027264,0.00007217424,0.00020832742,0.000068821566,0.00029214798,0.00034153412,0.00009892401,0.00001608438],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007787458,0.0002572478,0.27751955,0.00016257085,0.00014286928,0.00016251064,0.0015442278,0.0000752312,0.01628596,0.11090093,0.017553777,0.57531726],"study_design_scores_gemma":[0.002250246,0.0009239923,0.7047239,0.00025510057,0.000028100996,0.000051288298,0.00030182465,0.02652706,0.07494798,0.019663977,0.16860159,0.0017249358],"about_ca_topic_score_codex":0.000026061507,"about_ca_topic_score_gemma":0.0000046573305,"teacher_disagreement_score":0.7484823,"about_ca_system_score_codex":0.000034656376,"about_ca_system_score_gemma":0.00002944771,"threshold_uncertainty_score":0.41890612},"labels":[],"label_agreement":null},{"id":"W68420151","doi":"","title":"Introducing Hippy: A Visualization Tool for Understanding the alpha-Helix Pair Interface.","year":2006,"lang":"en","type":"article","venue":"BIOCOMP","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Visualization; OpenGL; Computer science; Software; Computer graphics (images); Interface (matter); Alpha helix; Helix (gastropod); Human–computer interaction; Crystallography; Programming language; Artificial intelligence; Operating system; Chemistry","score_opus":0.012009940199654562,"score_gpt":0.26413974466119033,"score_spread":0.25212980446153577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W68420151","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17789093,0.00048579936,0.82031965,0.00040645534,0.00020454435,0.0004168793,0.000018382629,0.000023410796,0.00023397837],"genre_scores_gemma":[0.9964677,0.000008301749,0.0021045632,0.00021336491,0.0006445387,0.000038638686,0.00016017588,0.000019123885,0.00034357785],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993424,0.000030167175,0.00015133971,0.00023409356,0.0000683311,0.00017371001],"domain_scores_gemma":[0.99963444,0.000015895648,0.00006467737,0.00022985986,0.00003933644,0.000015787848],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015914465,0.00011038512,0.00008427218,0.000023161345,0.00014461686,0.00004586553,0.000134222,0.000088828536,0.0000060402303],"category_scores_gemma":[0.00003767534,0.00008183709,0.000065951244,0.000063779815,0.000048008875,0.000003322407,0.00006202403,0.000038641247,0.000002251691],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016402779,0.000044120206,0.0022553864,0.00005979878,0.00006533324,6.539352e-7,0.000086486936,0.0014185704,0.93803316,0.03582659,0.018959813,0.00308608],"study_design_scores_gemma":[0.002157127,0.000577986,0.0029908267,0.00006191197,0.000087420565,0.000034119275,0.00047062387,0.01510098,0.7432431,0.04242673,0.19200444,0.00084471167],"about_ca_topic_score_codex":0.000017169255,"about_ca_topic_score_gemma":0.000025528765,"teacher_disagreement_score":0.8185768,"about_ca_system_score_codex":0.00003568853,"about_ca_system_score_gemma":0.000026573416,"threshold_uncertainty_score":0.33372197},"labels":[],"label_agreement":null}]}