{"id":"W2007622263","doi":"10.4018/jssci.2010100106","title":"The Formal Design Models of a Set of Abstract Data Types (ADTs)","year":2010,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Abstract data type; Programming language; Set (abstract data type); Architectural pattern; Data type; Process (computing); Software; Theoretical computer science; Software design; Software development","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":[],"consensus_categories":[],"category_scores_codex":[0.003030347,0.00009234386,0.0001380574,0.0002057135,0.0001778727,0.0001860485,0.003667595,0.00003213331,0.000004687917],"category_scores_gemma":[0.0009901815,0.00006544562,0.00004575949,0.0003911454,0.0007206482,0.001620549,0.0007522819,0.0002574869,0.000001534255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001724595,"about_ca_system_score_gemma":0.0007398115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001435571,"about_ca_topic_score_gemma":0.000005271818,"domain_scores_codex":[0.9977505,0.00002839087,0.0005773693,0.0002132659,0.001260299,0.0001701882],"domain_scores_gemma":[0.9934818,0.001594098,0.0006111078,0.0002513847,0.003979241,0.00008233666],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006027984,0.00005924675,0.0003086735,0.000006194561,0.0000580021,0.00001036463,0.000603307,0.1624875,0.0003864231,0.05636492,0.0001837767,0.7794713],"study_design_scores_gemma":[0.0001043261,0.0001184273,0.002680875,0.00009312492,0.000007094858,0.0002401623,0.00007904978,0.8567302,0.002387259,0.1372696,0.0001965567,0.00009341509],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02435471,0.0002323227,0.9738816,0.0004364946,0.0009283854,0.00005311871,0.00001204479,0.000009142123,0.00009215409],"genre_scores_gemma":[0.8774776,0.00008827935,0.1222528,0.00006675424,0.0001048889,4.786676e-7,0.000001496415,0.000002721025,0.000004982239],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8531228,"threshold_uncertainty_score":0.6815366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0807480552929192,"score_gpt":0.3401398017177968,"score_spread":0.2593917464248776,"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."}}