{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.001715824,0.001751826,0.003031995,0.00165755,0.000301646,0.0007119581,0.00526483,0.002152347,0.0008509097],"category_scores_gemma":[0.002792933,0.001687764,0.001313878,0.001624879,0.0005309485,0.0005766434,0.001862214,0.001255395,0.0001537912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004904955,"about_ca_system_score_gemma":0.0008639714,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8590707,"about_ca_topic_score_gemma":0.3096092,"domain_scores_codex":[0.9906116,0.0006211973,0.00229717,0.00333405,0.00118561,0.0019504],"domain_scores_gemma":[0.9873218,0.00563159,0.001745629,0.004299372,0.0003892927,0.0006123208],"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":[0.00009743334,0.0004428891,0.002725497,0.002222008,0.004094694,0.00006347564,0.003252998,0.000222122,0.0001345097,0.01280371,0.9660197,0.007920986],"study_design_scores_gemma":[0.002580499,0.0005081238,0.0006800555,0.00142763,0.001154723,0.00005534119,0.0005527763,0.002453571,0.001315606,0.03083821,0.9553449,0.003088551],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00033281,0.005322886,0.3860647,0.0002433704,0.002356736,0.001723886,0.6028276,0.0007775026,0.0003505346],"genre_scores_gemma":[0.01862925,0.0002356964,0.2118838,0.0004399425,0.002305003,0.0008148138,0.7638999,0.001047028,0.000744604],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5494615,"threshold_uncertainty_score":0.9995227,"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."}}