{"id":"W6922395646","doi":"10.12755/isec.res.2019.179","title":"THE POTENTIAL OF KNOWLEDGE MANAGEMENT ON CONSTRUCTION SITES","year":2019,"lang":"en","type":"dataset","venue":"NRCT Data Center","topic":"Educational Robotics and Engineering","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Process (computing); Variety (cybernetics); Multidisciplinary approach; Order (exchange); Phase (matter); Personal knowledge management; Quarter (Canadian coin); Investment (military)","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":[],"consensus_categories":[],"category_scores_codex":[0.0001680493,0.0001165254,0.0001048243,0.00007589928,0.00005870951,0.0001045963,0.002189059,0.00004851551,0.00001573175],"category_scores_gemma":[0.00001224135,0.00007570597,0.00003204797,0.00008742632,0.00002783964,0.0001319856,0.001073119,0.0001379569,0.0002474301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002673893,"about_ca_system_score_gemma":0.00003057496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003941016,"about_ca_topic_score_gemma":0.000004911737,"domain_scores_codex":[0.9991506,0.00001978622,0.0001719203,0.0002957141,0.0002185698,0.0001433585],"domain_scores_gemma":[0.997898,0.00005721237,0.00008635175,0.001889784,0.00004120575,0.00002746053],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001852545,0.00005166117,0.000004817056,0.00008058392,0.00004739132,0.00000114507,0.000003133317,0.0001228099,0.000001409441,0.003215414,0.9931923,0.003277487],"study_design_scores_gemma":[0.00009280959,0.00001478633,0.0001737055,0.00007096044,0.00001522949,0.000004783805,0.000007987046,0.003560447,0.000002795483,0.0000485378,0.9959232,0.00008473411],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000004511122,0.0001225427,0.009644401,0.0002570456,0.004672929,0.0001422283,0.9846282,0.00001111983,0.0005170386],"genre_scores_gemma":[0.0001499939,0.0005074001,0.003427281,0.00004688657,0.0001925399,0.000003403465,0.9954659,0.00000565446,0.0002009837],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01083767,"threshold_uncertainty_score":0.4067852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02902906653157603,"score_gpt":0.2757443718838415,"score_spread":0.2467153053522655,"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."}}