{"id":"W2259744366","doi":"","title":"Developing An Intelligent System For Modeling The Dam Behaviour Based On Statistical Pattern Matching Of Sensory Data","year":2006,"lang":"en","type":"article","venue":"Proceedings of the Joint CIB W78, W102, ICCCBE, ICCC, and DMUCE International Conference on Computing and Decision Making in Civil and Building Engineering, Montreal, Canada, 14-16 June","topic":"Dam Engineering and Safety","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Data mining; Statistical model; Computer science; Data acquisition; Matching (statistics); Data set; Set (abstract data type); Key (lock); Artificial intelligence; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00075121,0.0003257199,0.0004119504,0.0002119066,0.0001423957,0.0001500022,0.0004527435,0.00009340759,0.000001248466],"category_scores_gemma":[0.0001628701,0.0002499368,0.00004347698,0.0001279176,0.00004154986,0.0001200625,0.0002019907,0.0003289007,5.267624e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002034751,"about_ca_system_score_gemma":0.00007352702,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01119386,"about_ca_topic_score_gemma":0.01178709,"domain_scores_codex":[0.998028,0.00001110007,0.0006998163,0.0004468696,0.0004973747,0.0003168287],"domain_scores_gemma":[0.9988811,0.0004381072,0.0001733877,0.0002278551,0.0002026468,0.00007692129],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006971631,0.00003747181,0.001052297,0.0005490699,0.00004143909,0.00000438298,0.0001513846,0.9608948,0.0008536387,0.01389172,0.0003094338,0.0221446],"study_design_scores_gemma":[0.0004376112,0.00004065573,0.005311836,0.002617508,0.00002759624,0.00002152942,0.0002782411,0.9894136,0.0004928346,0.001014139,0.0000655136,0.0002789932],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5632274,0.0001550473,0.4352732,0.0001376316,0.0005992645,0.0002026802,0.0001409361,0.00007606589,0.0001877416],"genre_scores_gemma":[0.9898987,0.00004554763,0.009826008,0.00003374727,0.0001213714,0.00000823055,0.0000173444,0.00004112767,0.000007954686],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4266713,"threshold_uncertainty_score":0.9999953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0326422471308746,"score_gpt":0.2656651013124234,"score_spread":0.2330228541815488,"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."}}