{"id":"W4383219114","doi":"10.1109/dsp58604.2023.10167998","title":"Real-Time Crop Growth Stage Estimation Using Multi-modal Satellite Imagery","year":2023,"lang":"en","type":"article","venue":"","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; AUG Signals (Canada)","funders":"Agriculture and Agri-Food Canada","keywords":"Modal; Pixel; Robustness (evolution); Stage (stratigraphy); Computer science; Ground truth; Satellite; Estimation; Remote sensing; Artificial intelligence; Data mining; Geography; Engineering; Geology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000233793,0.0003235484,0.0002052134,0.0004799725,0.0001331372,0.000299197,0.0002529904,0.0002901763,0.000776222],"category_scores_gemma":[0.0006837545,0.0001718776,0.0003017765,0.0003688906,0.00009243365,0.0006083843,0.000218935,0.0002600934,0.0002863393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001871628,"about_ca_system_score_gemma":0.0002104209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00527922,"about_ca_topic_score_gemma":0.0126252,"domain_scores_codex":[0.9999053,0.00001607607,0.000003750787,0.00003531294,0.0000302583,0.000009232255],"domain_scores_gemma":[0.9997846,0.00008138212,0.00004607083,0.00002873114,0.00005099606,0.000008137578],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003329205,0.0001408136,0.03272779,0.0002082984,0.0001323561,0.00008727585,0.0001753328,0.2079829,0.3001648,0.0009747803,0.00122587,0.455847],"study_design_scores_gemma":[0.000009419932,0.0000605571,0.03437035,0.000008016611,0.00002469285,0.00005895408,0.00003228726,0.9271207,0.03658981,0.0005100418,0.001178849,0.00003634696],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2285854,0.0001323949,0.7681994,0.00005041088,0.00001899697,0.00004034744,0.0005098974,0.001285779,0.001177368],"genre_scores_gemma":[0.6446666,0.000125798,0.3529478,0.00002424731,0.00001387848,0.00004201995,0.0007273201,0.0001003791,0.001352059],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00527922,"threshold_uncertainty_score":0.01049697,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01857160097500591,"score_gpt":0.2578465854526797,"score_spread":0.2392749844776738,"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."}}