{"id":"W7129458160","doi":"10.1109/icecmsn68058.2025.11382946","title":"Deep Learning and Multi-Sensor Fusion for High-Resolution Crop Yield Forecasting","year":2025,"lang":"","type":"article","venue":"","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Deep learning; Stability (learning theory); Field (mathematics); Fusion; Baseline (sea); Precision agriculture; Artificial neural network; Scale (ratio); Crop yield","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005697737,0.0006804026,0.0003612843,0.0003897677,0.0001587859,0.000414369,0.000510052,0.0004911387,0.0007649765],"category_scores_gemma":[0.0008050826,0.0002433217,0.0004339675,0.0005869757,0.0001812604,0.001171873,0.000607503,0.0007603317,0.0001970426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006187659,"about_ca_system_score_gemma":0.0004395376,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008403786,"about_ca_topic_score_gemma":0.009822855,"domain_scores_codex":[0.9998519,0.00002550474,0.000008980611,0.00004461356,0.00003551588,0.00003345221],"domain_scores_gemma":[0.9998498,0.00004800727,0.0000214712,0.00002056121,0.00005009502,0.00001012479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001339759,0.0001302642,0.005028024,0.00007651737,0.0001276156,0.00007983363,0.00004779347,0.7572654,0.01403955,0.003097596,0.002056312,0.2179171],"study_design_scores_gemma":[0.000001608166,0.00001186159,0.0007229983,0.000002789563,0.000005339537,0.000005250633,0.000005715597,0.9959605,0.001740842,0.00123345,0.0003056572,0.000004033609],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1251469,0.001557505,0.8676373,0.0006771185,0.0001870968,0.00002977898,0.0005205582,0.00140414,0.002839502],"genre_scores_gemma":[0.9323041,0.0004049454,0.06508251,0.000108634,0.00005410302,0.00002299666,0.0004048612,0.0000264307,0.001591292],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008403786,"threshold_uncertainty_score":0.01670974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02124999502714154,"score_gpt":0.2388461744035422,"score_spread":0.2175961793764007,"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."}}