{"id":"W4398415249","doi":"10.7910/dvn/o7eggp/nwcvmq","title":"childmarr_5Feb2019CSVversion.tab","year":2019,"lang":"it","type":"dataset","venue":"Harvard Dataverse","topic":"interferon and immune responses","field":"Immunology and Microbiology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science","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":[0.001028126,0.002910982,0.001923159,0.00403064,0.001020197,0.00370398,0.003057716,0.003119145,0.1851186],"category_scores_gemma":[0.007683604,0.0009062985,0.001833032,0.005999193,0.000599407,0.001642711,0.002203105,0.001962691,0.171589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001692494,"about_ca_system_score_gemma":0.002276828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01782951,"about_ca_topic_score_gemma":0.02643427,"domain_scores_codex":[0.9990526,0.0001497471,0.00009243478,0.0003293421,0.0001877963,0.0001880818],"domain_scores_gemma":[0.997421,0.001060434,0.0002699779,0.0005639126,0.0003504184,0.0003342345],"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":[0.00007743444,0.00001567014,0.0006671862,0.0008038761,0.00003764475,0.00002299164,0.00001708967,0.0002204339,0.00008911086,0.0004050774,0.996125,0.001518277],"study_design_scores_gemma":[0.0004192664,0.00003182183,0.00315536,0.0003728645,0.00006226409,0.00009142509,0.00005204671,0.0005112439,0.0004252911,0.001761052,0.9930815,0.00003591961],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008598712,0.00009655998,0.00004123658,0.00007674638,0.00002065414,0.000005158125,0.9985857,0.0005247167,0.0005632839],"genre_scores_gemma":[0.0007036311,0.000109539,0.0001869969,0.0001157715,0.00001580788,0.00005805546,0.9977468,0.000205122,0.0008583058],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8148814,"threshold_uncertainty_score":0.6192836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0145160134190761,"score_gpt":0.2408012224679046,"score_spread":0.2262852090488285,"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."}}