{"id":"W6977826816","doi":"10.7479/4tbx-qm72","title":"DiversityScanner training and test insect images","year":2021,"lang":"en","type":"dataset","venue":"Museum für Naturkunde Berlin - Leibniz-Institut für Evolutions- und Biodiversitätsforschung","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Minnow Environmental (Canada)","funders":"","keywords":"Malaise; Training (meteorology); Taxon; Training set; Test (biology); Magnification; Image (mathematics)","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":[],"consensus_categories":[],"category_scores_codex":[0.0008061563,0.004190659,0.00144186,0.003487777,0.0008546803,0.001346124,0.002259772,0.002200896,0.01852593],"category_scores_gemma":[0.00173523,0.0006843187,0.00177725,0.002594209,0.0005942182,0.0010913,0.001622227,0.001519554,0.02649859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00143477,"about_ca_system_score_gemma":0.001041269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0138714,"about_ca_topic_score_gemma":0.03898723,"domain_scores_codex":[0.9988143,0.00008850201,0.00007791617,0.0004431533,0.0003644222,0.0002117387],"domain_scores_gemma":[0.9993831,0.00009566073,0.00004470318,0.0002216496,0.000188345,0.00006656766],"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":[0.0005269219,0.0005616503,0.006595818,0.001805179,0.0002527541,0.0004484386,0.000102565,0.004051548,0.006649658,0.0006293122,0.8805323,0.09784397],"study_design_scores_gemma":[0.0004079123,0.0004206329,0.04810419,0.0007824977,0.0002377053,0.002115757,0.0004241749,0.03203014,0.02394654,0.001834049,0.8895082,0.0001882198],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.02555594,0.002876566,0.003901273,0.0002690256,0.0004772349,0.000483589,0.9403455,0.01489456,0.01119636],"genre_scores_gemma":[0.008177294,0.0002292893,0.005542361,0.00009793327,0.00002127153,0.0002304714,0.9829015,0.000275311,0.002524705],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01852593,"threshold_uncertainty_score":0.06197542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03286453996700561,"score_gpt":0.284347864189566,"score_spread":0.2514833242225604,"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."}}