{"id":"W3123189130","doi":"","title":"Information Technology and Organizational Slack","year":2004,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Intellectual Capital and Performance Analysis","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Productivity; Productivity paradox; Investment (military); Information technology; Economics; Industrial organization; Business; Macroeconomics; Computer science","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":[0.001462182,0.0002002199,0.000192583,0.001734949,0.001079964,0.002306252,0.0002332426,0.000452148,0.007707556],"category_scores_gemma":[0.00651555,0.000100576,0.000151913,0.001931,0.002653385,0.001705613,0.002687107,0.0006147262,0.0004458293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001412419,"about_ca_system_score_gemma":0.001717543,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009121356,"about_ca_topic_score_gemma":0.001524131,"domain_scores_codex":[0.998862,0.0003736479,0.00007157979,0.00008693196,0.0001822288,0.0004236675],"domain_scores_gemma":[0.9853637,0.005304072,0.005026578,0.000450805,0.0007610222,0.003093784],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005887871,0.0008397492,0.5232112,0.0004055676,0.0001218913,0.001040477,0.008553597,0.004201586,0.001761948,0.2960459,0.004521915,0.1587074],"study_design_scores_gemma":[0.0001153361,0.0006098465,0.6624689,0.0005164244,0.00006546333,0.0008532261,0.01297593,0.002921021,0.0008295636,0.2776327,0.04096609,0.00004545947],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9231034,0.003350549,0.002326067,0.003623605,0.00007474298,0.00002884995,0.0001502944,0.00001643115,0.06732611],"genre_scores_gemma":[0.9981288,0.0004870309,0.0001613928,0.0001231048,0.00003716001,0.000009293946,0.00003223313,0.000002550569,0.001018498],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007707556,"threshold_uncertainty_score":0.02578437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003229312056563334,"score_gpt":0.1777430482578803,"score_spread":0.174513736201317,"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."}}