{"id":"W2518224280","doi":"10.5376/ijh.2015.05.0021","title":"Classical and Modern Methods for Characterization of Ornamental Crops","year":2016,"lang":"en","type":"article","venue":"International Journal of Horticulture","topic":"Flowering Plant Growth and Cultivation","field":"Agricultural and Biological Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ornamental plant; Characterization (materials science); Environmental science; Agroforestry; Biology; Agronomy; Horticulture; Materials science; Nanotechnology","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":[0.0001148408,0.00005346355,0.00009795247,0.0000111926,0.00002175546,0.000021184,0.0001147554,0.00004663436,0.00003488795],"category_scores_gemma":[0.0001269891,0.00001563245,0.00006251976,0.00003005676,0.00002693899,0.000174947,0.0000172467,0.00003368082,4.046787e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001879359,"about_ca_system_score_gemma":0.000005123476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001596738,"about_ca_topic_score_gemma":0.000004565685,"domain_scores_codex":[0.9994746,0.0000238115,0.0002341877,0.0000661611,0.0001410198,0.00006024887],"domain_scores_gemma":[0.9993258,0.0001060386,0.0002194364,0.000008860935,0.0002991002,0.00004083117],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001113159,0.00002989483,0.00201248,0.00000141626,0.00002746231,8.12512e-7,0.00004474689,2.629614e-7,0.7916743,0.000169637,0.00007249261,0.2058552],"study_design_scores_gemma":[0.001251953,0.0007502508,0.3753913,0.000235205,0.00005148646,0.000286596,0.0002097834,0.0003492643,0.5808958,0.00269831,0.03767176,0.0002083286],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9901339,0.00003220419,0.007015701,0.0024556,0.0002179818,0.00005498045,0.00006268251,0.000004123828,0.0000228216],"genre_scores_gemma":[0.9968399,0.00005208763,0.002622906,0.0000613474,0.0003076166,0.000001994649,0.00001900675,5.277536e-7,0.00009462569],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3733788,"threshold_uncertainty_score":0.06374726,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01288779536689159,"score_gpt":0.2785100675783234,"score_spread":0.2656222722114318,"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."}}