{"id":"W2375699415","doi":"","title":"Seed Source Variation in Aggregate Fruit and Seed Traits of Liriodendron chinense Sarg.","year":2009,"lang":"en","type":"article","venue":"Seed","topic":"Botanical Research and Chemistry","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Horticulture; Variation (astronomy); Biology; Botany; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001838443,0.0000916259,0.0001544368,0.000007469779,0.00004687468,0.00002789745,0.0001124823,0.0001033933,0.00004312574],"category_scores_gemma":[0.0001429953,0.00003874325,0.00004112209,0.0002361857,0.00003884088,0.00006578348,0.00002738942,0.0001408384,0.000005815064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000195378,"about_ca_system_score_gemma":0.000009042793,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002391389,"about_ca_topic_score_gemma":0.0002577779,"domain_scores_codex":[0.9991632,0.00004019079,0.0001759036,0.0001971339,0.000190854,0.0002327005],"domain_scores_gemma":[0.9996598,0.00009695697,0.00006041001,0.00003519374,0.00003342657,0.000114228],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00007829371,0.00005430488,0.004680152,0.000005841341,0.000003604796,0.000002949837,0.00009528045,0.000003655838,0.9811984,0.00002289814,0.000007409726,0.01384723],"study_design_scores_gemma":[0.0002950101,0.000177477,0.9767646,0.00002796513,0.000003225868,0.000003119986,0.00005224341,0.0003928683,0.02119929,0.0008037838,0.0001924432,0.00008803442],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974758,0.0001653388,0.000003392165,0.001509348,0.000007704207,0.00009650094,0.00001178174,0.00002379729,0.0007063429],"genre_scores_gemma":[0.9992059,0.00005024367,0.00004024512,0.0001346341,0.00006306227,0.000001684963,0.00001278539,5.730467e-7,0.0004908319],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9720844,"threshold_uncertainty_score":0.1579904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01066415456910139,"score_gpt":0.2216661927687948,"score_spread":0.2110020381996934,"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."}}