{"id":"W6979971232","doi":"","title":"Applicability of digital photography in monitoring changes of leaf inclination and foliage clumping with time","year":2024,"lang":"en","type":"dissertation","venue":"DSpace repository (University of Tartu)","topic":"Leaf Properties and Growth Measurement","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Toronto; Eesti Teadusfondi","keywords":"Aerial photography; Photography; Digital data; Stage (stratigraphy); Digital image analysis","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":[],"consensus_categories":[],"category_scores_codex":[0.0001131995,0.0001065847,0.0002534143,0.00004318906,0.00006457715,0.00001422339,0.0001127703,0.000113477,0.000006639013],"category_scores_gemma":[0.000005928957,0.00005806422,0.00006831883,0.0002337497,0.00007610142,0.000109034,0.00004154088,0.0001009163,4.838771e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002974206,"about_ca_system_score_gemma":0.00001322563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001195049,"about_ca_topic_score_gemma":0.001138011,"domain_scores_codex":[0.9993128,0.00002628981,0.0001150786,0.0002283111,0.0002271742,0.00009039672],"domain_scores_gemma":[0.9995539,0.00003420792,0.0002091429,0.00005511505,0.0001152415,0.00003241155],"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":[0.000544152,0.0002044479,0.1082388,0.001354414,0.0001259888,0.00001308003,0.005693216,0.000007001917,0.8635082,0.00001455968,0.00003049009,0.02026563],"study_design_scores_gemma":[0.0004922643,0.001357435,0.7736439,0.002275017,0.0002278664,0.000003736063,0.05181726,0.0001388493,0.1684469,0.00009783727,0.001007427,0.0004916098],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976425,0.0005102648,4.850509e-7,0.00009591245,0.00005250971,0.0002159674,0.00001707741,0.00001183431,0.001453409],"genre_scores_gemma":[0.9990426,0.0000672065,0.00003381251,5.437095e-7,0.00002619457,8.454659e-7,0.0000388842,0.000001229258,0.0007887393],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6950613,"threshold_uncertainty_score":0.236779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01034338377369177,"score_gpt":0.1760547424991499,"score_spread":0.1657113587254581,"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."}}