{"id":"W2362827489","doi":"","title":"Teh Analysis of and Spatial Distribution Pattern of Camellia rubimuricata Population","year":2010,"lang":"en","type":"article","venue":"Seed","topic":"Environmental Changes in China","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Camellia; Biology; Horticulture","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001810436,0.00008177743,0.0001482719,0.001582684,0.000220513,0.0002026741,0.0002299669,0.0001124491,0.001039978],"category_scores_gemma":[0.0002610731,0.00006683095,0.0002644002,0.0009401037,0.0001581348,0.0001373135,0.000193486,0.0001029051,0.00009777179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003929246,"about_ca_system_score_gemma":0.0001635502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00930755,"about_ca_topic_score_gemma":0.01322203,"domain_scores_codex":[0.9998978,0.000009547402,0.000007562909,0.00004423971,0.00001985368,0.00002096387],"domain_scores_gemma":[0.9997885,0.00004013122,0.00005635154,0.00001843868,0.00006047563,0.00003620095],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002535206,0.00004658088,0.806027,0.00006435024,0.0001050726,0.0003866717,0.0007668183,0.0009940064,0.1705234,0.0004184239,0.000284574,0.02012948],"study_design_scores_gemma":[0.000001890395,0.00002118781,0.9977019,8.91347e-7,0.00001054667,0.0000696807,0.00008353061,0.00081492,0.001063638,0.00001987274,0.0002097467,0.000002114942],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988353,0.00004323028,0.0002378339,0.000007565774,0.000001391433,0.000002951105,0.0002657612,0.000006647862,0.000599433],"genre_scores_gemma":[0.999047,0.00001468228,0.000150571,0.000005150046,0.00000156178,0.000004466878,0.0003485492,0.000001649478,0.000426413],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00930755,"threshold_uncertainty_score":0.01850677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006175221710378079,"score_gpt":0.2257669493301918,"score_spread":0.2195917276198137,"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."}}