{"id":"W4398607998","doi":"10.7910/dvn/mjkdys/mtar78","title":"replication psrm.smcl","year":2019,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Replication (statistics); Computer science; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005783226,0.002524372,0.002309132,0.008483939,0.001804702,0.005589461,0.003571162,0.002707872,0.3153738],"category_scores_gemma":[0.04767051,0.001366865,0.002427415,0.01123899,0.001074859,0.002435379,0.003774933,0.002499832,0.2268693],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001604809,"about_ca_system_score_gemma":0.007181195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01600495,"about_ca_topic_score_gemma":0.02582761,"domain_scores_codex":[0.9957815,0.0008510951,0.0007240516,0.00137128,0.0008373293,0.00043464],"domain_scores_gemma":[0.9723101,0.01205906,0.001706151,0.007624967,0.005024566,0.001275173],"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":[0.00008910071,0.00001597931,0.001108044,0.001021449,0.00008252846,0.00001788526,0.00004122099,0.0001235812,0.0001453763,0.0005171469,0.995027,0.001810579],"study_design_scores_gemma":[0.0006431697,0.00003664519,0.004045088,0.0006342859,0.0001362242,0.00005944675,0.0001076682,0.0002102259,0.0004874561,0.002783397,0.9907969,0.00005939184],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004476148,0.00003043788,0.00008142889,0.00007095495,0.0000322731,0.00001553188,0.9989035,0.0004239608,0.0003971764],"genre_scores_gemma":[0.0005934769,0.00005866502,0.0005276978,0.000129588,0.00003135753,0.0002244937,0.9968387,0.0004647205,0.001131249],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3153738,"threshold_uncertainty_score":0.9765362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01855981135952079,"score_gpt":0.2515346284821862,"score_spread":0.2329748171226654,"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."}}