{"id":"W4353085796","doi":"10.3389/fphy.2023.1101274","title":"PlotCam: A handheld proximal phenomics platform","year":2023,"lang":"en","type":"article","venue":"Frontiers in Physics","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Phenomics; Computer science; Sensor fusion; Data collection; Artificial intelligence; Population; Point cloud; Remote sensing; Computer vision; Environmental science; Real-time computing; Mathematics; Geography; Statistics; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001085836,0.0001463343,0.0001654971,0.00002689279,0.00007775171,0.00003278807,0.0002304172,0.00008272236,0.00002037505],"category_scores_gemma":[0.00001797344,0.0001258353,0.00005465582,0.0007278306,0.0001231343,0.0002214074,0.0001663736,0.0002066699,0.0006252964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002514011,"about_ca_system_score_gemma":0.000008634051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004504891,"about_ca_topic_score_gemma":0.0000209891,"domain_scores_codex":[0.9989218,0.00001429673,0.0001500279,0.0002917282,0.0002541482,0.0003680768],"domain_scores_gemma":[0.999636,0.00001480629,0.00005308773,0.0002301608,0.00000403637,0.00006189811],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004706084,0.0001379856,0.1043273,0.00002205557,0.00002947832,0.00005395158,0.003414508,0.02403743,0.004535435,0.0002685365,0.6974921,0.1656342],"study_design_scores_gemma":[0.002984838,0.0002475218,0.218923,0.0001558099,0.00006225995,0.00002142539,0.003196942,0.3960763,0.01590565,0.150881,0.2094069,0.002138323],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9510286,0.00003032076,0.006265424,0.0003261706,0.002012155,0.0005261783,0.00001590576,0.0003755595,0.03941972],"genre_scores_gemma":[0.9170053,0.0001256226,0.07280409,0.0005985116,0.001047454,0.00001748503,0.0001477512,0.0001141581,0.008139661],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4880852,"threshold_uncertainty_score":0.8037129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01086420190619182,"score_gpt":0.2007987753771553,"score_spread":0.1899345734709635,"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."}}