{"id":"W2945321286","doi":"10.1016/j.biosystemseng.2019.04.024","title":"A novel image processing algorithm to separate linearly clustered kiwifruits","year":2019,"lang":"en","type":"article","venue":"Biosystems Engineering","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":127,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"Northwest A and F University","keywords":"Calyx; Line (geometry); Hue; Segmentation; Cluster (spacecraft); Artificial intelligence; Mathematics; Computer science; Algorithm; Horticulture; Computer vision; Biology; Geometry","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":[0.0002949425,0.0008488856,0.0006518084,0.001907454,0.0005742293,0.001158129,0.001300844,0.001009213,0.003291929],"category_scores_gemma":[0.0004958804,0.0004067852,0.0008872776,0.001345184,0.0003453199,0.0007904521,0.0007328211,0.0008993919,0.002284143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005162686,"about_ca_system_score_gemma":0.0009379291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005137668,"about_ca_topic_score_gemma":0.01008066,"domain_scores_codex":[0.9997616,0.00001057553,0.00001203502,0.00006525107,0.0001061434,0.00004425875],"domain_scores_gemma":[0.9997181,0.00003887502,0.00002458724,0.00003482505,0.0001617733,0.00002184944],"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":[0.0001758475,0.00009737913,0.000764759,0.000116235,0.00006568435,0.00008135035,0.00007524086,0.00839885,0.2879243,0.00263405,0.003434221,0.6962321],"study_design_scores_gemma":[0.00003978728,0.0001528103,0.005397459,0.00002659088,0.0001216408,0.0005192059,0.00009788179,0.7058101,0.2635264,0.002520328,0.02171504,0.00007275469],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01757661,0.000212328,0.9784661,0.0001006355,0.00007024776,0.00008241968,0.0001330235,0.001759604,0.001599138],"genre_scores_gemma":[0.05601931,0.0002063094,0.9375755,0.00008387924,0.00004473158,0.00009186994,0.0005011463,0.0002337497,0.005243474],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005137668,"threshold_uncertainty_score":0.01101261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008414266281900567,"score_gpt":0.1905915190677458,"score_spread":0.1821772527858452,"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."}}