{"id":"W3171152275","doi":"10.13031/aim.202001444","title":"&amp;lt;i&amp;gt;Development of an integrated sensor system for automated on-the-spot measurement of physical soil properties&amp;lt;/i&amp;gt;","year":2020,"lang":"en","type":"article","venue":"2020 ASABE Annual International Virtual Meeting, July 13-15, 2020","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Penetrometer; Precision agriculture; Computer science; Tractor; Environmental science; Agricultural engineering; Remote sensing; Soil water; Agriculture; Engineering; Soil science; Automotive engineering; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0007349776,0.00068183,0.0004193196,0.0007464293,0.0003498457,0.0007967828,0.001332239,0.0005102482,0.02153406],"category_scores_gemma":[0.0008775427,0.0003263897,0.0002178759,0.0004407071,0.000364313,0.0006884959,0.0006014268,0.0005802222,0.008333433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005100406,"about_ca_system_score_gemma":0.0009328587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002756049,"about_ca_topic_score_gemma":0.003911547,"domain_scores_codex":[0.9993285,0.00005042297,0.00002541754,0.000132255,0.0004096468,0.00005383758],"domain_scores_gemma":[0.9994586,0.00006894859,0.00004532215,0.00006828857,0.000296086,0.00006284208],"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":[0.0005721434,0.0002873882,0.003901688,0.0003123,0.00004363636,0.0004969233,0.0002207317,0.00398146,0.591437,0.002964365,0.06574951,0.3300327],"study_design_scores_gemma":[0.0003082524,0.002694945,0.01468623,0.0001042512,0.00008021108,0.001384738,0.0001333316,0.1537361,0.6072937,0.001131881,0.2182602,0.0001862338],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05508474,0.0002094799,0.8584703,0.0005794063,0.0004681894,0.001615735,0.003639056,0.04333703,0.03659618],"genre_scores_gemma":[0.226193,0.0002585158,0.6824233,0.000770412,0.0001236513,0.001358518,0.005295456,0.001639131,0.08193792],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02153406,"threshold_uncertainty_score":0.07203859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03549504821868182,"score_gpt":0.2515192442006696,"score_spread":0.2160241959819878,"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."}}