{"id":"W7098847268","doi":"","title":"Read All about it!! What Happens Following a Technology Shock?,” mimeo","year":2004,"lang":"en","type":"article","venue":"","topic":"Image Processing and 3D Reconstruction","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Productivity; Field (mathematics); Technological change; Capital (architecture); Business cycle; Empirical research; Component (thermodynamics); Empirical evidence","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":[0.0001528218,0.0001312167,0.0001483968,0.0002180138,0.0001714915,0.0005195701,0.0005680386,0.0001297577,0.00001590824],"category_scores_gemma":[0.00002888644,0.0001141945,0.00008008857,0.0004793182,0.00006894563,0.001650426,0.0001604765,0.0001697711,0.0002028109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005130334,"about_ca_system_score_gemma":0.0001410005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003656821,"about_ca_topic_score_gemma":0.00003853114,"domain_scores_codex":[0.9988976,0.00001221936,0.0001967084,0.0004001734,0.0001588035,0.0003344596],"domain_scores_gemma":[0.9994061,0.00001442925,0.00005901404,0.0004081683,0.0000529314,0.00005937656],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000002539647,0.00006408709,0.0002340872,0.00001686029,0.00004701036,0.00008942156,0.0009127987,0.00007632349,0.004655877,0.04676347,0.000451852,0.9466857],"study_design_scores_gemma":[0.006443734,0.0006361049,0.0004235996,0.00252091,0.0001309989,0.004840693,0.005738248,0.03094618,0.337007,0.4635276,0.1447391,0.003045881],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03904488,0.001544167,0.9162708,0.02326537,0.001894116,0.0001256098,1.65293e-7,0.001129248,0.01672563],"genre_scores_gemma":[0.6797253,0.0001125232,0.3161497,0.001711461,0.00006467376,0.0000137275,0.000001354406,0.00001311036,0.002208205],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9436398,"threshold_uncertainty_score":0.5010227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01202031358606795,"score_gpt":0.2567165936203695,"score_spread":0.2446962800343015,"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."}}