{"meta":{"query_hash":"3a1e10b43d59","filters":{"venue":"International Journal of Computers in Clinical Practice"},"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/3a1e10b43d59","api":"https://metacan.xera.ac/api/v1/cohort?venue=International+Journal+of+Computers+in+Clinical+Practice"},"results":[{"id":"W2899183792","doi":"10.4018/ijccp.2018070101","title":"A Biologically-Inspired Metaheuristic Approach for the Simultaneous Generation of Alternatives","year":2018,"lang":"en","type":"article","venue":"International Journal of Computers in Clinical Practice","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Firefly algorithm; Benchmark (surveying); Metaheuristic; Computer science; Mathematical optimization; Artificial intelligence; Machine learning; Mathematics","score_opus":0.14264015778157074,"score_gpt":0.43382820613745265,"score_spread":0.2911880483558819,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2899183792","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":[0.01333891,0.000284606,0.98222995,0.00026166526,0.00003563988,0.00010923738,0.000029294682,0.00011047161,0.003600199],"genre_scores_gemma":[0.21394752,0.00027039688,0.7836378,0.00014287193,0.00002514771,0.000393316,0.00006328697,0.000040488598,0.0014791503],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994531,0.00027377345,0.000024545445,0.00006278584,0.00014574442,0.00004004846],"domain_scores_gemma":[0.99907076,0.0006913987,0.00009081836,0.000048527723,0.00006881687,0.000029532806],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014709164,0.0009607843,0.00072097237,0.0012449619,0.0007010725,0.00087187724,0.0014720057,0.0014342108,0.0014027294],"category_scores_gemma":[0.0026825378,0.0005311278,0.0012567532,0.0010974209,0.0012236405,0.0007228708,0.0010312594,0.0015537625,0.00016165074],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022528764,0.000041235886,0.00025543157,0.0000651731,0.000051112875,0.00004939702,0.000060809805,0.94251204,0.001975675,0.02825273,0.0003841059,0.026329724],"study_design_scores_gemma":[0.000013715194,0.000040013936,0.000042549505,0.000014167683,0.000012981371,0.00002512337,0.000013611836,0.9882422,0.000576301,0.010100156,0.00091294735,0.000006183408],"about_ca_topic_score_codex":0.0026164602,"about_ca_topic_score_gemma":0.003128512,"teacher_disagreement_score":0.0026164602,"about_ca_system_score_codex":0.0013350702,"about_ca_system_score_gemma":0.0016755253,"threshold_uncertainty_score":0.009686649},"labels":[],"label_agreement":null}]}