{"id":"W1508207627","doi":"","title":"Towards Temporal Reasoning Using Qualitative Probabilities","year":2002,"lang":"en","type":"article","venue":"","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Probabilistic logic; Axiom; Abstraction; Causality (physics); Qualitative reasoning; Computer science; Set (abstract data type); Constant (computer programming); Theoretical computer science; Probabilistic relevance model; Probability distribution; Temporal logic; Artificial intelligence; Mathematics; Algorithm; Probabilistic analysis of algorithms; Statistics; Programming language","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":[0.0001816639,0.00006619519,0.00007149641,0.00005834715,0.00009554126,0.0001109702,0.0001273823,0.00002575866,0.0005427415],"category_scores_gemma":[0.0000652029,0.00005915845,0.00003050864,0.0002087216,0.00004260882,0.0005537645,0.00004782855,0.00004788291,0.00002854962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004727238,"about_ca_system_score_gemma":0.00002507667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001097204,"about_ca_topic_score_gemma":0.00001882099,"domain_scores_codex":[0.9993505,0.0000827074,0.000135494,0.0001711622,0.0001398165,0.0001202549],"domain_scores_gemma":[0.9996537,0.00003650256,0.00004315827,0.0001556925,0.00006779157,0.00004313242],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001942769,0.00005224436,0.001657879,0.00001639278,0.00001931662,0.000004591341,0.06037217,0.002824795,0.0001036865,0.8217251,0.001094259,0.1121277],"study_design_scores_gemma":[0.0001458903,0.00002477931,0.0003296962,0.00001250968,0.000001761141,0.00001677064,0.002235004,0.9919402,0.0002015542,0.004310589,0.0006399142,0.0001413592],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009801436,0.00002301728,0.957341,0.0008809941,0.0001263394,0.00008304112,6.02415e-7,0.0002033372,0.03154028],"genre_scores_gemma":[0.5490816,0.000002148565,0.4499972,0.0001149093,0.00001345757,0.000002307808,4.399383e-7,0.000002366813,0.0007855088],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9891154,"threshold_uncertainty_score":0.5942639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07442154708020235,"score_gpt":0.3150522443592541,"score_spread":0.2406306972790518,"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."}}