{"id":"W7092283429","doi":"10.58052/iej9b068e","title":"6_RGHR_V1 Individual Sample Plant Structure bog labrador tea seeds","year":2024,"lang":"","type":"other","venue":"System for Earth Sample Registration (SESAR)","topic":"Tea Polyphenols and Effects","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Bog; Sample (material); Vegetation (pathology); Population structure; Peat","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":[0.0007651235,0.0007224642,0.0006617098,0.001883645,0.0007568456,0.001086241,0.0009684916,0.0005234226,0.1116357],"category_scores_gemma":[0.002000649,0.0006159557,0.0005087121,0.001539703,0.000225824,0.0006700599,0.00115312,0.0004147352,0.08879476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005901477,"about_ca_system_score_gemma":0.001124592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01347236,"about_ca_topic_score_gemma":0.0233136,"domain_scores_codex":[0.9994352,0.00005627385,0.00003981526,0.0001957975,0.0001923416,0.00008061594],"domain_scores_gemma":[0.9987909,0.0001878331,0.0001081795,0.0004789201,0.0003435386,0.00009060133],"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":[0.002849884,0.0002553022,0.02926226,0.001129458,0.0001363511,0.0003050888,0.0007065761,0.002772351,0.07241487,0.004290034,0.6087575,0.2771204],"study_design_scores_gemma":[0.0002425002,0.0001674284,0.07070417,0.00007242444,0.00009884003,0.0003383363,0.0002606888,0.004988385,0.05701825,0.001880827,0.8641388,0.0000893602],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.04149835,0.0001920221,0.03780328,0.0002102229,0.00007581008,0.000438465,0.7794804,0.0799347,0.06036684],"genre_scores_gemma":[0.06178044,0.0001336396,0.06877156,0.00009999129,0.00003224545,0.0005641317,0.8160928,0.01727531,0.03524975],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1116357,"threshold_uncertainty_score":0.3734587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02442583947084456,"score_gpt":0.2685131547304932,"score_spread":0.2440873152596486,"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."}}