{"id":"W2096736443","doi":"10.3138/cjpe.17.002","title":"The Temporal Logic Model Concept","year":2002,"lang":"en","type":"article","venue":"Canadian Journal of Program Evaluation","topic":"Complex Systems and Decision Making","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Interim; Computer science; Documentation; Logic model; Temporal logic; Context (archaeology); Adaptation (eye); Accountability; Process (computing); Temporal logic of actions; Duration (music); Space (punctuation); Artificial intelligence; Programming language; Interval temporal logic; Sociology; Psychology; Political science; Social science; History; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.009381101,0.00009739406,0.000205064,0.0003122178,0.0005459156,0.001012399,0.0007691639,0.0000576653,0.001111861],"category_scores_gemma":[0.005722967,0.00005436194,0.0001751942,0.0006003205,0.0001388561,0.0003142664,0.00001647363,0.0001784142,0.0001215914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001769478,"about_ca_system_score_gemma":0.0007634833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002705379,"about_ca_topic_score_gemma":0.01062205,"domain_scores_codex":[0.9959772,0.0004409303,0.001035075,0.0001697716,0.002093239,0.0002838256],"domain_scores_gemma":[0.9954776,0.0005671687,0.0007480641,0.0003764266,0.002402568,0.0004281917],"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":[0.000003785742,0.00001023077,0.001063145,3.147367e-7,0.000008869349,0.00001109823,0.0006729676,0.0128018,0.00000360351,0.006142259,0.08598892,0.893293],"study_design_scores_gemma":[0.0003062218,0.0001344808,0.001426267,0.00001450746,0.00001434164,0.00007830094,0.0006229226,0.7298859,0.000001780798,0.1446098,0.1228311,0.00007441043],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4070162,0.1248885,0.2745772,0.04129592,0.01860662,0.01065735,0.00007524237,0.0001405432,0.1227425],"genre_scores_gemma":[0.9952461,0.000002663886,0.002988399,0.0001391059,0.000207241,0.00001477965,3.982769e-7,0.000006733246,0.001394642],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8932186,"threshold_uncertainty_score":0.9998013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5968884418094136,"score_gpt":0.4888732088178995,"score_spread":0.1080152329915141,"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."}}