{"id":"W1787171477","doi":"10.1007/s11284-015-1307-x","title":"<i>LeafArea</i> : an R package for rapid digital image analysis of leaf area","year":2015,"lang":"en","type":"article","venue":"Ecological Research","topic":"Leaf Properties and Growth Measurement","field":"Agricultural and Biological Sciences","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Japan Society for the Promotion of Science; McGill University; National Institutes of Health; Adobe Systems","keywords":"Computer science; Directory; R package; Sample (material); Computer graphics (images); File format; Image file formats; Process (computing); Digital image; Artificial intelligence; Computer vision; Image (mathematics); Pattern recognition (psychology); Image processing; Database; Computational science; Operating system","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002447231,0.0001173305,0.0003274244,0.00005187181,0.0001918895,0.0001633345,0.0005056754,0.0001239202,0.0009636182],"category_scores_gemma":[0.001752091,0.0000380462,0.0002136821,0.001075347,0.0002405778,0.0002329592,0.0001899013,0.0001809198,0.0000416424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007386802,"about_ca_system_score_gemma":0.00003046907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001000422,"about_ca_topic_score_gemma":0.0003650419,"domain_scores_codex":[0.9977868,0.0002259213,0.0002798858,0.000404521,0.0007383694,0.0005645507],"domain_scores_gemma":[0.9980397,0.0006240194,0.00005582614,0.0001352546,0.0007906261,0.0003545735],"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":[0.002361103,0.005559164,0.1007039,0.00005423004,0.000915513,0.00004825614,0.0008309404,0.00006608872,0.4260655,0.001724242,0.06004848,0.4016227],"study_design_scores_gemma":[0.001602031,0.02248019,0.741717,0.00002238289,0.0002652764,0.000003251469,0.007428502,0.0032949,0.02669284,0.006499978,0.1891311,0.0008625041],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9900223,0.0001076714,0.00002975341,0.001968466,0.00003806721,0.0004393955,0.0001739067,0.0000363588,0.007184065],"genre_scores_gemma":[0.9987941,0.00001763209,0.0001053016,0.0001178405,0.0001109697,0.00008091739,0.0001861941,0.000001099113,0.000585993],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6410131,"threshold_uncertainty_score":0.9999496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3197140651923762,"score_gpt":0.3625130201215918,"score_spread":0.04279895492921554,"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."}}