{"id":"W4398495833","doi":"10.7910/dvn/6me9uj","title":"Replication data for: The Impact of Open Access Mandates on Invention","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Research Data Management Practices","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Replication (statistics); Computer science; Internet privacy; Biology; Virology","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":["metaresearch","open_science"],"consensus_categories":[],"category_scores_codex":[0.004041506,0.001528379,0.001200375,0.004198283,0.001110131,0.003665228,0.003516907,0.002825625,0.06512629],"category_scores_gemma":[0.03298865,0.0007705483,0.00218287,0.007841849,0.0006273555,0.002504777,0.00333095,0.00345707,0.06411142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001851587,"about_ca_system_score_gemma":0.004612498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03553037,"about_ca_topic_score_gemma":0.06021085,"domain_scores_codex":[0.9973155,0.0004987275,0.0004116991,0.0004923347,0.0008983648,0.0003834719],"domain_scores_gemma":[0.9850529,0.003165328,0.001682118,0.004068744,0.00500387,0.001027106],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008212095,0.00001726139,0.001797561,0.0004388012,0.0000386278,0.00001531367,0.00002194467,0.0001580185,0.00005363548,0.00121288,0.9938164,0.002347369],"study_design_scores_gemma":[0.0006325565,0.00002920335,0.01181353,0.0004803854,0.00006435023,0.00008849195,0.0001438896,0.0005704367,0.0003457825,0.003501028,0.9822811,0.0000492467],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002764573,0.0001761227,0.0001218908,0.0006070003,0.0001623859,0.00001616596,0.997333,0.000304059,0.001002946],"genre_scores_gemma":[0.001655072,0.0001298065,0.0005927427,0.0002434104,0.00004932329,0.000126381,0.9960513,0.0001116623,0.001040333],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9964831,"threshold_uncertainty_score":0.2178692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3485174468271553,"score_gpt":0.4991545332233165,"score_spread":0.1506370863961612,"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."}}