{"id":"W6909117986","doi":"10.35078/0l4ltq/owf7g6","title":"Montreal B.jpg","year":2022,"lang":"en","type":"dataset","venue":"Repositório 1 da Fiocruz","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Set (abstract data type); Work (physics); Perspective (graphical); Focus (optics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009838406,0.005200082,0.002979008,0.00601201,0.001841494,0.00601498,0.005237323,0.003590273,0.1945486],"category_scores_gemma":[0.007242899,0.001314507,0.002010782,0.01041279,0.0008828271,0.003310625,0.00292512,0.002558001,0.3824929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00312744,"about_ca_system_score_gemma":0.003769818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1193831,"about_ca_topic_score_gemma":0.1677103,"domain_scores_codex":[0.9987639,0.0001860481,0.00006881975,0.0004796713,0.0002479375,0.0002536236],"domain_scores_gemma":[0.9978917,0.0003935685,0.0001206243,0.0007782108,0.0005348655,0.0002810087],"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":[0.00003363906,0.000006930436,0.0001052358,0.0002194189,0.00001314521,0.000006640394,0.00000611098,0.0001170212,0.00002858239,0.0002106532,0.9979758,0.001276758],"study_design_scores_gemma":[0.0001551655,0.00001448361,0.001120357,0.0002805293,0.00002359528,0.00003502043,0.00004309958,0.0005976561,0.0002461467,0.001463862,0.9959882,0.00003191607],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006696888,0.0001870062,0.00007672904,0.0001096216,0.00006661181,0.00000950155,0.9954698,0.002115685,0.00189804],"genre_scores_gemma":[0.0002577916,0.0001005407,0.0001860006,0.00005179685,0.00001414259,0.00002367255,0.9980764,0.000265908,0.001023749],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8054515,"threshold_uncertainty_score":0.6508298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0161509536677432,"score_gpt":0.2663071107819616,"score_spread":0.2501561571142183,"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."}}