{"id":"W2938910637","doi":"10.7451/cbe.2018.60.2.33","title":"Understanding the requirements for a blind-spot monitoring system on tractors from the operator’s perspective","year":2018,"lang":"en","type":"article","venue":"Canadian Biosystems Engineering","topic":"Agriculture and Farm Safety","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Perspective (graphical); Blind spot; Operator (biology); Computer science; Artificial intelligence; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0002563581,0.0001793749,0.0001425502,0.0000156079,0.0007310299,0.0001536762,0.0003490248,0.0001060675,0.00001013213],"category_scores_gemma":[0.00002965727,0.00005344842,0.00008768705,0.0002790939,0.00002823289,0.00007751624,0.0000154423,0.0001311297,0.00001802407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001032967,"about_ca_system_score_gemma":0.0000261984,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02756769,"about_ca_topic_score_gemma":0.04907657,"domain_scores_codex":[0.9989657,0.000033335,0.0001791023,0.0002645515,0.0001611207,0.0003961971],"domain_scores_gemma":[0.9993132,0.0002571866,0.00005222228,0.00009780761,0.00009033761,0.0001892126],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003495318,0.00009727882,0.02222564,0.0001483663,0.0015371,0.00006801539,0.0249553,0.001224365,0.6877562,0.2414434,0.01547095,0.004723882],"study_design_scores_gemma":[0.002704247,0.001936047,0.2234207,0.003204524,0.0003966186,0.0000754076,0.3979171,0.008736691,0.02634202,0.0002423818,0.3316039,0.003420403],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9912098,0.0003683353,0.000237354,0.001887387,0.003191831,0.001173838,0.0003731211,0.0001433603,0.001414959],"genre_scores_gemma":[0.9963479,0.000003110513,0.00001215912,0.00009298848,0.003417704,0.00005715525,0.00001597072,0.000003348347,0.00004963524],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6614141,"threshold_uncertainty_score":0.9789078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08419008388734064,"score_gpt":0.232058339972623,"score_spread":0.1478682560852823,"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."}}