{"id":"W2991111171","doi":"10.1016/j.cviu.2020.103045","title":"Open cross-domain visual search","year":2020,"lang":"en","type":"preprint","venue":"Computer Vision and Image Understanding","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Visual search; Computer science; Domain (mathematical analysis); Sketch; Semantic space; Space (punctuation); Function (biology); Semantic search; Multidimensional scaling; Artificial intelligence; Information retrieval; Machine learning; Search engine; Algorithm; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0007632652,0.0005179707,0.0006682348,0.0002806435,0.0005120987,0.007827933,0.003157057,0.0002577331,0.00002557798],"category_scores_gemma":[0.00003673305,0.0004768101,0.0001654483,0.0004305488,0.000271467,0.002105428,0.02554741,0.001062058,0.00003057838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003285985,"about_ca_system_score_gemma":0.0001833213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001509986,"about_ca_topic_score_gemma":7.676884e-7,"domain_scores_codex":[0.9965478,0.0002119994,0.0005339252,0.001629166,0.000540309,0.000536771],"domain_scores_gemma":[0.998229,0.0001884062,0.0002130198,0.0008404977,0.0001486686,0.0003804038],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004855568,0.0005885729,0.0004976013,0.001818405,0.0003564694,0.00229532,0.006900379,0.0001148887,0.0167215,0.4967352,0.04581086,0.4276752],"study_design_scores_gemma":[0.001788133,0.001253469,0.000570824,0.001118936,0.00001935788,0.0001132418,0.0002240733,0.3524799,0.008897955,0.6249847,0.00689483,0.001654535],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0007656657,0.00028563,0.9924294,0.00237487,0.000540469,0.0008137614,0.00001070991,0.0005930115,0.002186506],"genre_scores_gemma":[0.2161287,0.0003950431,0.7813327,0.001602012,0.0003289927,0.00001517032,0.00002844769,0.00005735395,0.0001116259],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4260207,"threshold_uncertainty_score":0.9997684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1189654997218815,"score_gpt":0.424251377539317,"score_spread":0.3052858778174355,"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."}}