{"id":"W4398630641","doi":"10.7910/dvn/dl4s2m/ayhjgx","title":"T3.do","year":2020,"lang":"it","type":"dataset","venue":"Harvard Dataverse","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Replication (statistics); Depression (economics); Great Depression; Psychology; Biology; Geography; Economics; Keynesian economics; Virology; Archaeology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002279976,0.001999762,0.002078437,0.003849446,0.0008236705,0.003998595,0.002969904,0.001978649,0.5796323],"category_scores_gemma":[0.01856085,0.001464195,0.001365109,0.006474229,0.0006124837,0.002608371,0.002909581,0.003014435,0.5740361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008847615,"about_ca_system_score_gemma":0.001933923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006426474,"about_ca_topic_score_gemma":0.01005217,"domain_scores_codex":[0.9980503,0.0005382005,0.0002468474,0.0005510713,0.0002776304,0.0003358955],"domain_scores_gemma":[0.9932632,0.00290766,0.0006046043,0.00192679,0.0007731185,0.0005247097],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004210003,0.000009649331,0.000308815,0.000239385,0.0000172914,0.000007768563,0.00001795934,0.0001049946,0.00003929532,0.0007563313,0.9951398,0.003316555],"study_design_scores_gemma":[0.0002669406,0.00001675065,0.0009774566,0.0002369986,0.00002843911,0.00003068483,0.00004890402,0.0004626165,0.0002576241,0.005412921,0.9922338,0.00002694457],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006964339,0.00004028828,0.0008250005,0.0001791677,0.0000504399,0.00003088494,0.9892718,0.00492835,0.004604416],"genre_scores_gemma":[0.002531108,0.0001939883,0.00426547,0.0006949732,0.000121632,0.0008974664,0.9700884,0.008612577,0.01259444],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4203677,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03131741978679353,"score_gpt":0.2088837670145025,"score_spread":0.1775663472277089,"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."}}