{"id":"W2767150407","doi":"10.1186/s13007-017-0244-9","title":"Microscope image based fully automated stomata detection and pore measurement method for grapevines","year":2017,"lang":"en","type":"article","venue":"Plant Methods","topic":"Plant Surface Properties and Treatments","field":"Agricultural and Biological Sciences","cited_by":73,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Wine Australia; South Australian Research and Development Institute; Institut de Recherche pour le Développement; Alberta Water Research Institute","keywords":"Skeletonization; Artificial intelligence; Segmentation; Microscope; Image processing; Computer science; Pattern recognition (psychology); Biological system; Computer vision; Image (mathematics); Materials science; Biology; Optics; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005468949,0.0005337248,0.0005550756,0.0009880244,0.000206132,0.000498201,0.0008797471,0.0007174063,0.001362693],"category_scores_gemma":[0.0008352972,0.0003708077,0.0005907684,0.0003798931,0.0001972885,0.00048546,0.000364184,0.0003173635,0.0007093266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003302327,"about_ca_system_score_gemma":0.0004129503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001658536,"about_ca_topic_score_gemma":0.002351303,"domain_scores_codex":[0.999557,0.0000410926,0.00002266429,0.0001782639,0.0001740024,0.0000270113],"domain_scores_gemma":[0.9992371,0.0001373959,0.0001054383,0.0001309516,0.0003507051,0.00003853452],"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":[0.0002372412,0.00008978462,0.004970501,0.0003121996,0.00006116978,0.0001960957,0.0001189209,0.008752128,0.7206642,0.0003669261,0.001332961,0.2628978],"study_design_scores_gemma":[0.0000408296,0.0006542737,0.05210907,0.00004418755,0.0001097028,0.001462192,0.0001014831,0.5917682,0.3471581,0.0006143877,0.005840795,0.00009668132],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2367063,0.0006361706,0.7549194,0.00006905365,0.00005365071,0.0001667369,0.0004055317,0.005541621,0.001501628],"genre_scores_gemma":[0.4340364,0.0003186947,0.5629352,0.00004733364,0.00002023343,0.0001091053,0.0006333715,0.0001545735,0.001745111],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001658536,"threshold_uncertainty_score":0.004558623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07618732634237924,"score_gpt":0.3435408048402556,"score_spread":0.2673534784978764,"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."}}