{"meta":{"query_hash":"e1ef5e4ee255","filters":{"venue":"Software Engineering"},"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/e1ef5e4ee255","api":"https://metacan.xera.ac/api/v1/cohort?venue=Software+Engineering"},"results":[{"id":"W2321807112","doi":"10.2316/journal.213.2013.2.213-1044","title":"COMPONENT-BASED DEVELOPMENT OF RUNTIME OBSERVERS IN THE COMDES FRAMEWORK","year":2013,"lang":"en","type":"article","venue":"Software Engineering","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Component (thermodynamics); Computer science; Physics","score_opus":0.012850377687018808,"score_gpt":0.20362768848426457,"score_spread":0.19077731079724577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2321807112","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008698071,0.00007338025,0.9865574,0.00003412274,0.000025826756,0.00013540231,0.000034215904,0.0032345483,0.0012070532],"genre_scores_gemma":[0.19457763,0.00018540668,0.79995316,0.000045985038,0.000014385215,0.0002617023,0.00020067768,0.00068882405,0.004072237],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986999,0.00028868666,0.000114634124,0.00026507274,0.0005253648,0.000106238156],"domain_scores_gemma":[0.99846965,0.0005305383,0.00018232543,0.00040720715,0.00034506165,0.00006518353],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022762886,0.0007198701,0.00047740218,0.00043430476,0.0002982512,0.0009322757,0.0014631832,0.0006111559,0.0017536117],"category_scores_gemma":[0.003247386,0.0006946923,0.0008751075,0.00014935141,0.00071925257,0.0009744234,0.0010829892,0.00107693,0.00048085998],"study_design_candidate":"not_applicable","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":[0.00083920686,0.00043967977,0.007360004,0.0010957372,0.00025044853,0.0015098924,0.0013121819,0.2995731,0.17464136,0.20336185,0.0045073493,0.3051091],"study_design_scores_gemma":[0.0001418781,0.00027046143,0.0007476469,0.00013871818,0.000107772255,0.00040063297,0.00007338398,0.7577247,0.17127264,0.010833108,0.05822833,0.000060745566],"about_ca_topic_score_codex":0.0019747326,"about_ca_topic_score_gemma":0.0030205688,"teacher_disagreement_score":0.0022762886,"about_ca_system_score_codex":0.0006159178,"about_ca_system_score_gemma":0.0016104799,"threshold_uncertainty_score":0.0120382905},"labels":[],"label_agreement":null},{"id":"W4248677059","doi":"10.2316/journal.213.2015.4.213-1071","title":"TEST CLUSTER SELECTION USING COVER COEFFICIENTS","year":2015,"lang":"en","type":"article","venue":"Software Engineering","topic":"Educational Technology and Assessment","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Selection (genetic algorithm); Cover (algebra); Statistics; Test (biology); Cluster (spacecraft); Mathematics; Computer science; Artificial intelligence; Biology; Engineering; Ecology","score_opus":0.019854221089585376,"score_gpt":0.2629163778824063,"score_spread":0.24306215679282092,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4248677059","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24946134,0.0006380846,0.74080527,0.00031273635,0.000044235367,0.00040450905,0.00064996455,0.002601046,0.005082761],"genre_scores_gemma":[0.83152795,0.00020431922,0.16435535,0.000078139834,0.0000578121,0.000274375,0.0016677633,0.00045278226,0.0013815238],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9961332,0.0006807853,0.00018697759,0.0006031633,0.0019060785,0.0004897806],"domain_scores_gemma":[0.98716354,0.007199802,0.0011056395,0.0011251214,0.0029435034,0.0004623998],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025444734,0.0011799717,0.001630104,0.00988021,0.0011073727,0.002022335,0.001359169,0.0014169755,0.0022312137],"category_scores_gemma":[0.027788494,0.00050634384,0.0012442442,0.004230089,0.00077916746,0.0016918104,0.0018743023,0.0009248508,0.00091223035],"study_design_candidate":"simulation_or_modeling","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":[0.00079663715,0.0002789647,0.032123014,0.0003184206,0.0002909662,0.00052654423,0.00054604,0.3181184,0.030113503,0.010696941,0.0076674926,0.598523],"study_design_scores_gemma":[0.000029197194,0.00011651099,0.006047172,0.000028533901,0.00005410994,0.00023211296,0.000114716146,0.97859436,0.00803998,0.0052778935,0.0014359218,0.000029495053],"about_ca_topic_score_codex":0.006785322,"about_ca_topic_score_gemma":0.005997154,"teacher_disagreement_score":0.00988021,"about_ca_system_score_codex":0.0014467197,"about_ca_system_score_gemma":0.001588777,"threshold_uncertainty_score":0.01349169},"labels":[],"label_agreement":null}]}