{"id":"W4404729960","doi":"10.1145/3686397.3686411","title":"iHSPRec: Image Enhanced Historical Sequential Pattern Recommendation","year":2024,"lang":"en","type":"article","venue":"","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Image (mathematics); Artificial intelligence; Computer vision; Information retrieval","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001845406,0.00008604191,0.00007685494,0.00009087447,0.00005258754,0.0003159095,0.0003268373,0.00004727991,0.0004718245],"category_scores_gemma":[0.00001552481,0.00007182872,0.00006298043,0.0003099729,0.0000131676,0.0007249466,0.0001007666,0.0001129028,0.0004245498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002940492,"about_ca_system_score_gemma":0.00004457745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004085026,"about_ca_topic_score_gemma":0.000001873338,"domain_scores_codex":[0.999173,0.00004136968,0.0001827201,0.0003199274,0.0001419668,0.0001410428],"domain_scores_gemma":[0.9995921,0.00004050975,0.00002586788,0.0002324833,0.00006006182,0.00004902448],"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":[8.571612e-7,0.00002156739,0.000001940311,0.0000161366,0.000005407262,0.000004321979,0.0001033515,1.849178e-8,0.09222582,0.008573433,0.01745483,0.8815923],"study_design_scores_gemma":[0.00006493463,0.00005781578,0.00004897685,0.00001820812,0.000004831879,0.00001105362,0.00000572113,0.03643017,0.7377186,0.003959862,0.221484,0.000195798],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00006593247,0.00005190951,0.9730423,0.007860332,0.0007982237,0.00008224997,0.000001149565,0.001314228,0.01678367],"genre_scores_gemma":[0.9026064,0.00008688722,0.08033042,0.0006786263,0.0002588881,0.00004913696,0.00001934929,0.00001707719,0.01595315],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9025405,"threshold_uncertainty_score":0.545687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02356295276577371,"score_gpt":0.2856333248039211,"score_spread":0.2620703720381474,"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."}}