{"id":"W6931591510","doi":"10.5683/sp3/ff6ai9","title":"Navigating Stats Can Data &amp; Scrubbing Data Clean with Excel Workshop","year":2024,"lang":"en","type":"dataset","venue":"Borealis","topic":"Cell Adhesion Molecules Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; University of Guelph","funders":"","keywords":"Upload; Data visualization; Hoist (device); Carving; NetCDF; Data archive; Data format","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007176906,0.001473371,0.001026851,0.004255448,0.001232856,0.004499616,0.001712298,0.0007903742,0.1244255],"category_scores_gemma":[0.02959362,0.001045832,0.001382154,0.005170004,0.0007510315,0.002513481,0.004128801,0.00297754,0.1780365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001050242,"about_ca_system_score_gemma":0.003909088,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008574388,"about_ca_topic_score_gemma":0.01926452,"domain_scores_codex":[0.9961044,0.0008760878,0.0005864915,0.0007284433,0.001427377,0.0002771697],"domain_scores_gemma":[0.9865035,0.004623853,0.0007546566,0.004397998,0.002698802,0.001021205],"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":[0.00005135678,0.0000134209,0.0005353604,0.0001312485,0.00001509601,0.00002145961,0.0000626965,0.00007418622,0.0001415798,0.0008945965,0.9880238,0.01003542],"study_design_scores_gemma":[0.00007372363,0.00001209742,0.001493905,0.0001396629,0.00001372298,0.00002975152,0.0001250823,0.0005307025,0.001167526,0.003643531,0.992732,0.00003825162],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0008571355,0.0002005845,0.01172294,0.001921732,0.000464168,0.0003189508,0.878275,0.08026271,0.02597685],"genre_scores_gemma":[0.009883525,0.000387337,0.04991358,0.003068689,0.000202882,0.002194531,0.8749499,0.03306839,0.02633106],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1244255,"threshold_uncertainty_score":0.4162448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1349713072001481,"score_gpt":0.4136519416876052,"score_spread":0.2786806344874571,"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."}}