{"id":"W4411414079","doi":"10.69554/bxip3397","title":"Avoiding disastrous data-based decisions: The secret to meaningful workplace insights","year":2025,"lang":"en","type":"article","venue":"Corporate real estate journal","topic":"BIM and Construction Integration","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Workplace Health, Safety and Compensation Commission","funders":"","keywords":"Overconfidence effect; Ingenuity; Quality (philosophy); Decision quality; Key (lock); Data quality; Nomothetic and idiographic; Computer science; Real estate; Data science; Risk analysis (engineering); Management science; Knowledge management; Business; Marketing; Psychology; Engineering; Economics; Computer security; Finance","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05404558,0.0009378216,0.001063893,0.003150915,0.008077404,0.03121696,0.00353398,0.00722933,0.004419018],"category_scores_gemma":[0.08219519,0.0009035751,0.0008966386,0.002546845,0.04559105,0.03995312,0.02017478,0.01136506,0.00175347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004302559,"about_ca_system_score_gemma":0.01379862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001564778,"about_ca_topic_score_gemma":0.001975487,"domain_scores_codex":[0.9512878,0.0316581,0.001847913,0.002102025,0.01082901,0.002275218],"domain_scores_gemma":[0.8943997,0.07370071,0.004873788,0.01519241,0.00740405,0.004429394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001314498,0.0002423087,0.003910935,0.001098421,0.00008676707,0.001055571,0.09779767,0.002443591,0.002218266,0.6378942,0.0297405,0.2233805],"study_design_scores_gemma":[0.0000226893,0.00006996667,0.0007129668,0.001161994,0.00001831395,0.0003807446,0.0612802,0.001743963,0.0009832352,0.7775496,0.1560064,0.00006994725],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.06234409,0.01312546,0.2941001,0.4890037,0.002869278,0.0003915994,0.0003224849,0.0005708761,0.1372724],"genre_scores_gemma":[0.7772031,0.009174106,0.1809873,0.01987976,0.001201991,0.000417536,0.0002689434,0.0002727962,0.01059449],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.05404558,"threshold_uncertainty_score":0.2858237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04140121606694259,"score_gpt":0.2604750077955436,"score_spread":0.219073791728601,"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."}}