{"id":"W6975860027","doi":"10.60510/awfwi03450","title":"IGSN AWFWI03450 (EN22040-TG06): Individual Sample (Biology, leaf for DNA analyses) of sample EN22040-T06 from Ogilvie Mountains (Nahoni Range), Yukon, CA","year":2024,"lang":"en","type":"other","venue":"GFZ IGSN Sample Catalogue","topic":"Real-Time Systems Scheduling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Sample (material); DNA","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":[],"consensus_categories":[],"category_scores_codex":[0.0007297463,0.001462079,0.001096096,0.005070526,0.001735752,0.001218296,0.002156071,0.001058582,0.1787146],"category_scores_gemma":[0.001656434,0.0007656461,0.0005377224,0.01009241,0.0004454767,0.0007405321,0.001274499,0.0006068866,0.1658951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002549981,"about_ca_system_score_gemma":0.004362902,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1759887,"about_ca_topic_score_gemma":0.3008089,"domain_scores_codex":[0.9991399,0.00003389874,0.00005708099,0.0002910011,0.0002732138,0.0002048718],"domain_scores_gemma":[0.9980834,0.0000996356,0.0001350392,0.0005858591,0.0008773978,0.0002187146],"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":[0.0004389652,0.00008036091,0.01030841,0.0007210541,0.00003965847,0.00009688849,0.0005407583,0.0005921587,0.01375498,0.002286024,0.9159879,0.05515296],"study_design_scores_gemma":[0.00005411626,0.0000379402,0.04007871,0.00007309289,0.00003832078,0.0001027819,0.0002434532,0.0003479851,0.004749541,0.0007749964,0.9534693,0.0000296276],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.006823104,0.00006920716,0.003221339,0.00005716999,0.00005063966,0.0001329238,0.9552677,0.002981659,0.0313963],"genre_scores_gemma":[0.005021938,0.00005235188,0.00508973,0.00005235793,0.00001275111,0.0002040547,0.9738209,0.002206934,0.01353887],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8240113,"threshold_uncertainty_score":0.5978601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06678584560943426,"score_gpt":0.3304699592395422,"score_spread":0.2636841136301079,"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."}}