{"id":"W2939361545","doi":"10.1002/col.22375","title":"Color characteristics of Beijing's regional woody vegetation based on Natural Color System","year":2019,"lang":"en","type":"article","venue":"Color Research & Application","topic":"Phytochemicals and Antioxidant Activities","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Species richness; Hue; Color space; Beijing; Vegetation (pathology); Principal component analysis; Color analysis; Geography; Botany; Ecology; Mathematics; Biology; Statistics; Artificial intelligence; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.0006843567,0.0001313087,0.0003381502,0.0002215665,0.00009850199,0.00002465985,0.0001604885,0.000113375,0.00001493576],"category_scores_gemma":[0.0001615929,0.00011587,0.00008460747,0.0004163602,0.0001675719,0.00008380858,0.00003895715,0.0003800208,0.0001560565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003037955,"about_ca_system_score_gemma":0.0002287259,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001473277,"about_ca_topic_score_gemma":0.000002160489,"domain_scores_codex":[0.998097,0.0001004046,0.0003169672,0.0003541108,0.0008275308,0.000304003],"domain_scores_gemma":[0.9981779,0.0005038081,0.0001830334,0.0003977378,0.0006319996,0.0001055393],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001618022,0.000375822,0.003798678,0.001187768,0.00002878526,0.000003568307,0.00006428815,0.00002759895,0.9840756,0.005748685,0.000502694,0.00256847],"study_design_scores_gemma":[0.003675275,0.002323876,0.3276202,0.001650275,0.00007403254,0.00002179287,0.0005917239,0.3603031,0.2945634,0.0001234177,0.00868497,0.0003678707],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946443,0.00005386546,0.0001413989,0.0008806514,0.00007092436,0.001885839,0.00001735751,0.00006290107,0.002242803],"genre_scores_gemma":[0.9983091,0.00001212763,0.000254615,0.0001200727,0.0001745044,0.0004940025,0.0002188563,0.00002402746,0.0003927351],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6895122,"threshold_uncertainty_score":0.4725043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02962590776554352,"score_gpt":0.3426458595984783,"score_spread":0.3130199518329347,"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."}}