{"id":"W6968865432","doi":"10.5281/zenodo.3790135","title":"Lasionycta gelida Crabo & Lafontaine 2009, sp. n.","year":2009,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Video Analysis and Summarization","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Holotype; Seta; Dorsum; Taxonomy (biology); Lobe","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":[0.0001518731,0.000752854,0.000358793,0.00170705,0.002358471,0.0007441789,0.0007368536,0.0007235736,0.05467095],"category_scores_gemma":[0.0005471215,0.0002574076,0.0001691056,0.00152217,0.001052873,0.001493516,0.0008723846,0.001055365,0.01633833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003266628,"about_ca_system_score_gemma":0.001761424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1209065,"about_ca_topic_score_gemma":0.2836324,"domain_scores_codex":[0.9998273,0.00001654269,0.00001152531,0.0000616163,0.00005902086,0.00002393047],"domain_scores_gemma":[0.9996915,0.00005582148,0.00009707764,0.00002713433,0.0001012701,0.00002716451],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002396494,0.00004732794,0.009907015,0.000809695,0.00003458583,0.001738038,0.001391876,0.000297203,0.006932607,0.005100652,0.2621948,0.7113066],"study_design_scores_gemma":[0.00003533735,0.00003593072,0.04202802,0.0007206517,0.00002801903,0.001766304,0.001024562,0.0001256095,0.0007602016,0.0004925425,0.9529657,0.00001716753],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0402546,0.0153402,0.00307784,0.002652111,0.0006619742,0.0004495446,0.009382427,0.001044447,0.927137],"genre_scores_gemma":[0.5376607,0.01651694,0.01070957,0.003732717,0.00060195,0.001167718,0.007738902,0.000468767,0.4214026],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1209065,"threshold_uncertainty_score":0.2404054,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02906425313525837,"score_gpt":0.2432270048461881,"score_spread":0.2141627517109297,"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."}}