{"id":"W2995126905","doi":"10.2139/ssrn.3468822","title":"Could Machine Learning Be a General-Purpose Technology? Evidence from Online Job Postings","year":2019,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Firm Innovation and Growth","field":"Economics, Econometrics and Finance","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Online learning; Computer science; Psychology; Data science; World Wide Web","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":[0.004118909,0.0002025518,0.0003311978,0.001697502,0.0009367883,0.002614852,0.0008816998,0.00171389,0.02726918],"category_scores_gemma":[0.04397917,0.0002320773,0.0003396524,0.002458591,0.00120806,0.003956527,0.001248683,0.001602766,0.004568845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004682158,"about_ca_system_score_gemma":0.0004776648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005066501,"about_ca_topic_score_gemma":0.005584195,"domain_scores_codex":[0.9978269,0.0009815913,0.0001461021,0.0002378064,0.0004841702,0.0003234784],"domain_scores_gemma":[0.8536825,0.1054269,0.02335997,0.007039959,0.006672515,0.003818129],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001709965,0.002208705,0.808163,0.0005931965,0.0002585068,0.0006731265,0.004929646,0.001129849,0.001086465,0.01020797,0.01440857,0.154631],"study_design_scores_gemma":[0.0001289487,0.0007210112,0.9555625,0.000368403,0.0001650116,0.0003369063,0.0078517,0.003036231,0.001627738,0.008636269,0.02151238,0.0000529162],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9498903,0.001052418,0.001252589,0.00766308,0.000126233,0.00007532451,0.001795919,0.00004851647,0.03809571],"genre_scores_gemma":[0.9914821,0.0006802853,0.0004325546,0.0005512771,0.0001959866,0.00002410448,0.0005941994,0.00001835156,0.00602118],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02726918,"threshold_uncertainty_score":0.09122449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02212641194417593,"score_gpt":0.233914376741695,"score_spread":0.2117879647975191,"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."}}