{"id":"W6888490768","doi":"10.21227/rd1e-6k71","title":"RSSdata_HumanHuman","year":2020,"lang":"en","type":"dataset","venue":"IEEE DataPort","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Guelph","funders":"","keywords":"RSS; Identification (biology); Data collection; Table (database); Set (abstract data type)","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":[0.0008081098,0.004217829,0.001818313,0.003173576,0.000836172,0.001396998,0.002985337,0.002434139,0.02179915],"category_scores_gemma":[0.003277416,0.0005824671,0.001317979,0.004768761,0.00051272,0.001331418,0.001800221,0.001561237,0.05062418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009790647,"about_ca_system_score_gemma":0.001594468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02403558,"about_ca_topic_score_gemma":0.04246246,"domain_scores_codex":[0.9984741,0.0002469705,0.0001818477,0.0003524308,0.0005240277,0.0002206108],"domain_scores_gemma":[0.9982091,0.0003526512,0.0001149858,0.0005813648,0.0005355212,0.0002064866],"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":[0.0001515647,0.000080246,0.001096793,0.0006930326,0.00004764722,0.00007051863,0.000033704,0.0008835066,0.0006304311,0.0003170838,0.9882994,0.007696167],"study_design_scores_gemma":[0.0003365315,0.0001839786,0.01278363,0.0002774155,0.00008113425,0.0005248264,0.0002786343,0.004821727,0.003313011,0.001483052,0.9757789,0.0001371567],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001366377,0.0001901826,0.0004435554,0.0001119654,0.0001217549,0.00003594802,0.9934716,0.002567556,0.001691081],"genre_scores_gemma":[0.001101859,0.00006698626,0.0004432843,0.00003743853,0.00001096963,0.00004733974,0.9975673,0.00006354858,0.0006611843],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9782009,"threshold_uncertainty_score":0.07292539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0649428489772638,"score_gpt":0.3175334129313685,"score_spread":0.2525905639541047,"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."}}