{"id":"W4393710646","doi":"10.5281/zenodo.2658725","title":"Mental imagery data from words","year":2019,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Mental image; Computer science; Psychology; Cognitive psychology; Artificial intelligence; Cartography; Geography; Neuroscience; Cognition","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":[0.0006938501,0.002418379,0.001174971,0.004168766,0.0008543932,0.001724387,0.002291107,0.001899572,0.02399848],"category_scores_gemma":[0.004643423,0.0004276973,0.001155537,0.003925617,0.000681793,0.001158151,0.002524053,0.00146444,0.04947294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009498196,"about_ca_system_score_gemma":0.001842933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01022025,"about_ca_topic_score_gemma":0.02162569,"domain_scores_codex":[0.9988041,0.0001623956,0.0002085875,0.0003228609,0.0003345665,0.000167457],"domain_scores_gemma":[0.9981187,0.0003445761,0.0001699101,0.0005563099,0.0006211704,0.0001892659],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005954905,0.0002573201,0.003276645,0.002638235,0.0001047546,0.0002143876,0.0001808942,0.0007226993,0.002493395,0.0009846344,0.9615297,0.02700197],"study_design_scores_gemma":[0.0004559188,0.000184887,0.02058122,0.0005485183,0.0001125885,0.0006109624,0.0005990005,0.001958805,0.004666171,0.001648514,0.9685259,0.0001075185],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004646371,0.0004113539,0.0005332712,0.0001110296,0.0001127021,0.000137909,0.9905064,0.00106538,0.002475667],"genre_scores_gemma":[0.002608417,0.00008632372,0.0006212564,0.00003501658,0.00001163637,0.0002551959,0.9952226,0.00004855005,0.001111105],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02399848,"threshold_uncertainty_score":0.08028287,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08424705287499723,"score_gpt":0.2956746136513079,"score_spread":0.2114275607763106,"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."}}