{"id":"W2759584423","doi":"10.3758/s13428-018-1097-5","title":"Quaddles: A multidimensional 3-D object set with parametrically controlled and customizable features","year":2018,"lang":"en","type":"article","venue":"Behavior Research Methods","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"Canadian Institutes of Health Research","keywords":"Computer science; Object (grammar); Scripting language; Feature (linguistics); Set (abstract data type); Artificial intelligence; Task (project management); Computer vision; Feature vector; Human–computer interaction; Parametric statistics; Scratch; Pattern recognition (psychology); Programming language; Mathematics","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":[0.0005794195,0.001009201,0.001202196,0.0009735261,0.0003816732,0.001139307,0.003351053,0.000810534,0.007140902],"category_scores_gemma":[0.002496186,0.001080993,0.001744171,0.000651661,0.000687153,0.001282976,0.003841706,0.001009739,0.001496541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004913372,"about_ca_system_score_gemma":0.0007266381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002454479,"about_ca_topic_score_gemma":0.003933524,"domain_scores_codex":[0.9995301,0.00008053537,0.00003402189,0.0001325875,0.0001849949,0.00003770242],"domain_scores_gemma":[0.9991486,0.0003213623,0.00006392952,0.0002469527,0.00009208133,0.0001270277],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001307374,0.0008110625,0.005401005,0.001980042,0.0006118946,0.0008918727,0.001202637,0.122246,0.2341054,0.03466567,0.03063722,0.5661398],"study_design_scores_gemma":[0.0002340528,0.000663551,0.006274196,0.0001241739,0.0001644963,0.001325605,0.0001651345,0.856153,0.06357953,0.02649029,0.04460768,0.0002182584],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02692548,0.0002002609,0.962325,0.0001574492,0.0001030714,0.0003485713,0.001880772,0.006532407,0.001526959],"genre_scores_gemma":[0.1636125,0.0003128006,0.8275393,0.0002264226,0.00003088718,0.000843356,0.003212764,0.001657026,0.002565028],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007140902,"threshold_uncertainty_score":0.02388871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1729737641991413,"score_gpt":0.5344835669519601,"score_spread":0.3615098027528187,"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."}}