{"id":"W6950710979","doi":"10.5683/sp3/m4amgv","title":"Turkey Point Flux Station 1939 Forest (TP4)","year":2014,"lang":"en","type":"dataset","venue":"Borealis","topic":"Advanced Electron Microscopy Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Chronosequence; Taiga; Boreal; Carbon sink; Carbon flux; Deciduous; Temperate climate; Sink (geography); Carbon sequestration; Carbon cycle","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009795774,0.0002543276,0.0001937997,0.00004688284,0.00009707292,0.00003099858,0.0003301412,0.0003490661,0.0000338224],"category_scores_gemma":[0.00004498604,0.000249737,0.00009837191,0.00005595309,0.00006349954,0.000002574996,0.000102884,0.0001853465,0.00001565552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003132617,"about_ca_system_score_gemma":0.00007808885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003918988,"about_ca_topic_score_gemma":0.005742255,"domain_scores_codex":[0.9988936,0.00003203816,0.0002409828,0.000442059,0.0001137451,0.0002776299],"domain_scores_gemma":[0.9987699,0.000008903683,0.0001865631,0.000865806,0.00008935104,0.0000794443],"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":[0.00001576477,0.00003084651,0.000001723339,0.00002664541,0.00001912744,7.246511e-7,0.000001362765,0.00002642252,0.01974399,0.00009060352,0.9794677,0.0005750632],"study_design_scores_gemma":[0.0001264289,0.0001740304,0.00001761724,0.0000155249,0.00003305653,0.00000813366,0.000003068917,0.000008420858,0.0314188,0.0005167907,0.967408,0.0002701494],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004975221,0.0002043686,0.0212015,0.0001236975,0.00003243061,0.0003184313,0.9777257,0.00003187272,0.0003122803],"genre_scores_gemma":[0.0001016181,0.0007611984,0.002448777,0.0005598151,0.0003944092,0.0001931541,0.9950937,0.0000353768,0.0004119715],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01875273,"threshold_uncertainty_score":0.9999955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006363547066374496,"score_gpt":0.302033333713832,"score_spread":0.2956697866474575,"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."}}