{"id":"W3122328332","doi":"10.1111/iere.12375","title":"NETWORK SEARCH: CLIMBING THE JOB LADDER FASTER","year":2018,"lang":"en","type":"preprint","venue":"International Economic Review","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Position (finance); Wage; Climb; Climbing; Labour economics; Quality (philosophy); Economics; Network structure; Hill climbing; Computer science; Microeconomics; Engineering; Distributed computing; Artificial intelligence","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":[0.0007339792,0.0002177478,0.0006075094,0.0007234187,0.0005271336,0.001060278,0.0007664564,0.0009610577,0.01425859],"category_scores_gemma":[0.005644108,0.0002479025,0.0005195428,0.000622194,0.000754836,0.002684943,0.000799621,0.0008003527,0.000912379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006279455,"about_ca_system_score_gemma":0.000363795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003863933,"about_ca_topic_score_gemma":0.002954277,"domain_scores_codex":[0.9997608,0.00009245278,0.000006924845,0.00005475076,0.00002720884,0.00005793139],"domain_scores_gemma":[0.9979625,0.001001657,0.000411159,0.0002337574,0.000114941,0.0002760357],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0006991407,0.0004121938,0.02308335,0.000458011,0.0002016481,0.0005762257,0.001045665,0.3302501,0.005237613,0.5584537,0.02026279,0.05931955],"study_design_scores_gemma":[0.0001410299,0.0001136073,0.01093558,0.00007667183,0.00004382203,0.0001670766,0.0003630929,0.5352864,0.0006259277,0.4467597,0.005454294,0.00003273665],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7927628,0.001585909,0.1697822,0.005669375,0.000133257,0.00006542191,0.0005348063,0.0003560612,0.02911021],"genre_scores_gemma":[0.986426,0.0003926866,0.006819671,0.0002471196,0.0000424641,0.00003048405,0.0001081627,0.00003860571,0.005894834],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01425859,"threshold_uncertainty_score":0.04769975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08806640717710802,"score_gpt":0.3029070653650686,"score_spread":0.2148406581879606,"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."}}