{"id":"W4398913998","doi":"10.7910/dvn/zbrtjh","title":"Replication Data for: Beyond the Unit Root Question: Uncertainty and Inference","year":2019,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Replication (statistics); Inference; Root (linguistics); Unit root; Computer science; Mathematics; Statistics; Artificial intelligence; Linguistics; Philosophy","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001425232,0.000321803,0.0003042852,0.00008948899,0.0002773959,0.0006173975,0.005897763,0.000254526,0.0001651126],"category_scores_gemma":[0.0008177815,0.0002454577,0.00004000975,0.0002287945,0.000140041,0.0009813264,0.003015729,0.0004672735,0.003741365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003526484,"about_ca_system_score_gemma":0.0003676562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000307896,"about_ca_topic_score_gemma":0.0002975852,"domain_scores_codex":[0.9973751,0.0001669912,0.0003691469,0.001408232,0.0003540263,0.0003265136],"domain_scores_gemma":[0.9866313,0.0004877989,0.0003035144,0.01224571,0.0002121011,0.0001195149],"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":[0.00001047301,0.00002168359,0.000007514127,0.00007649395,0.00002545593,0.000002070969,0.00001450615,0.00008926074,0.000002215646,0.01025557,0.9852598,0.004234992],"study_design_scores_gemma":[0.0001977802,0.00005734359,0.00003682843,0.00008232125,0.00006712237,0.00001610736,0.000007449098,0.06962566,0.000002560933,0.002564638,0.9270447,0.0002974771],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000005584789,0.000009157632,0.2314364,0.0001680991,0.0004340794,0.0004080667,0.7674497,0.00005715049,0.00003170851],"genre_scores_gemma":[0.0001468649,0.0003780122,0.00396291,0.0007975627,0.0001758105,0.00005614153,0.994307,0.00001157797,0.000164091],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2274735,"threshold_uncertainty_score":0.9999998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07338997824271198,"score_gpt":0.3310777180133337,"score_spread":0.2576877397706217,"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."}}